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Dissertations / Theses on the topic 'Meta-data-analysis'
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Lin, Wen. "Meta analysis methods for microarray data and proteomics data." Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1692119641&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
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Nik, Idris Nik Ruzni. "Estimating meta analysis parameters in non-standard data." Thesis, University of Strathclyde, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.432097.
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Simmonds, Mark Crawford. "Statistical methods for individual patient data meta-analysis." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.595824.
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Shin, In-Soo. "Same author and same data dependence in meta-analysis." Tallahassee, Florida : Florida State University, 2009. http://etd.lib.fsu.edu/theses/available/etd-06222009-185532/.
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Thesis (Ph. D.)--Florida State University, 2009.Advisor: Betsy Jane Becker, Florida State University, College of Education, Dept. of Educational Psychology and Learning Systems. Title and description from dissertation home page (viewed on Nov. 12, 2009). Document formatted into pages; contains xiii, 161 pages. Includes bibliographical references.
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Abo-Zaid, Ghada Mohammed Abdallah. "Individual patient data meta-analysis of prognostic factor studies." Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/3186/.
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Prognostic factors (PFs) are patient characteristics (e.g. age, biomarker levels) that are associated with future clinical outcomes in patients with a disease or health condition. Evidence-based PF results are paramount, for which individual patient data (IPD) meta-analysis is thought to be the ’gold-standard’ approach, as it synthesises the raw data across related studies (in contrast to an aggregate data meta-analysis, that just uses reported summary data). In this Ph.D. thesis, I investigate statistical issues and develop methodological recommendations for individual patient data meta-analysis of prognostic factor studies (IMPF) projects. First, I investigate the benefits and limitations of IPD meta-analyses of PF studies through a systematic review and in-depth evaluation of existing IPD meta-analyses of PFs; 48 IMPF articles were found and an in-depth evaluation of a random sample of 20 IMPF articles was undertaken to identify how such projects are initiated, conducted, and reported, and to identify the benefits and challenges of the IPD approach. I found that although IMPF articles have many advantages, they still face a number of challenges and pitfalls such as different methods of measurements, ignoring clustering of patients across studies, missing data, and potential publication bias, unachieved linearity assumption of PFs, poor reporting, and potentially not protocol driven. To improve IMPF articles and projects guidelines were developed, and an array of methodological research questions identified. Secondly, I undertook an empirical study to compare between the IPD and aggregated data approach to assess PFs in breast cancer. I showed that the IPD approach is preferable over aggregated data, as it allows one to adjust the PF by other confounding factors, examine PFs in subgroups of patients and assess the interaction between two PFs as an additional PF. It also allowed more studies and more patients to be included. However, the IPD approach still faced challenges, such as potential publication bias, missing data, and failed model assumptions in some studies. Thirdly, I developed eleven IPD meta-analysis models to investigate whether accounting for clustering of patients within studies should be undertaken and which approach is the best to use. The models differed by using either a one-step or two-step approach, and whether they accounted for parameter correlation and residual variation. An IPD meta-analysis of 4 studies for age as a PF for 6 month mortality in traumatic brain injury was used as an applied example. Surprisingly, I found that there was no difference between the eleven models because there was little variation in baseline risk across studies. Thus, a simulation study was undertaken to examine which model is the best one-step or two-step, and whether accounting for the clustering of patients within studies is important. I found that the clustering across studies should be considered, and one-step model accounting for the clustering of patients within studies is the best fitted model as it yielded the lowest bias and the coverage was around 95%. Ignoring clustering can produce downward bias and too low a coverage; occasionally the two-step produces too high a coverage. Fourthly, I examined the linearity assumption for the relation between age and risk of 6 months mortality in the traumatic brain injury dataset. I found that the linear trend was not the best in all studies. Thus, I developed three non-linear fractional polynomial IPD meta-analysis models based on whether one-step or two-step approach and whether first or second order fractional polynomial functions are performed. I found that one-step fractional polynomial meta-analysis model that account for the clustering of patients within studies is again the best fitted model, as it easier to fit and force the IPD studies to have the same polynomial powers. This revealed age has a quadratic relationship with mortality risk. Fifth, I assessed whether small-study effects (i.e. potential publication bias) exists for 6 IPD prognostic factor articles by using different tools, such as contour funnel plot, cumulative meta-analysis, trim and fill method, and regression tests. I found the small-study effects problem is not a major concern, in contrast to aggregated data meta-analysis of PFs. Only in the breast cancer data of Look et al. was there substantial evidence for small-study effects. However, adjusted results to account for this provided a smaller PF effect but suggested the original conclusions are unlikely to change. To sum up, this thesis highlights a number of challenges of IMPF projects and discusses possible approaches to dealing with some of them. However, numerous challenges remain for future work.
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Freeman, S. C. "One-step individual participant data network meta-analysis of time-to-event data." Thesis, University College London (University of London), 2017. http://discovery.ucl.ac.uk/1546292/.
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Network meta-analysis (NMA) combines direct and indirect evidence from trials to calculate and rank treatment effect estimates. While modelling approaches for continuous and binary outcomes are relatively well developed, less work has been done with time-to-event outcomes. Such outcomes have usually been analysed using Cox proportional hazard (PH) models, but in oncology, with longer follow-up of trials and time-dependent effects of targeted treatments, this may no longer be appropriate. Alongside this, NMA conducted in the Bayesian setting has been increasing in popularity. In this thesis I extend the work of Royston and Parmar to the NMA setting, showing that Royston-Parmar models, fitted in WinBUGS, provide a flexible, practical approach for Bayesian NMA with time-to-event data and can accommodate non-PH. Inconsistency in NMA occurs when the direct and indirect evidence are not in agreement with each other and can result in biased treatment effect estimates. It is therefore important that attempts are made to identify, understand and, where appropriate, adjust for inconsistency. In this thesis I consider four increasingly complex methods of assessing inconsistency in NMA, proposed (relatively) recently in the literature. Motivated by individual participant data (IPD) from 42 trials comparing radiotherapy, sequential and concomitant chemotherapy from 7531 people with lung cancer, I illustrate why one of these approaches may be misleading and propose an alternative approach. Stratified medicine aims to identify groups of patients most likely to respond to treatment. However, many trials are underpowered to detect clinically meaningful differences in subgroups. NMA models fitted with treatment-covariate interactions potentially have greater power to identify such differences. In the final part of this thesis I extend the one-step IPD NMA Royston-Parmar model to include treatment-covariate interactions, providing practical guidance on how to deal with missing covariate data and how to combine or separate within and across trial information.
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Holzhauer, Björn [Verfasser]. "Meta-analysis of aggregate data on medical events / Björn Holzhauer." Magdeburg : Universitätsbibliothek, 2017. http://d-nb.info/1149124334/34.
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Tudur, Smith Catrin. "Individual patient data meta-analysis with time-to-event outcomes." Thesis, University of Liverpool, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.406660.
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Samartsidis, Pantelis. "Point process modelling of coordinate-based meta-analysis neuroimaging data." Thesis, University of Warwick, 2016. http://wrap.warwick.ac.uk/87635/.
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Now over 25 years old, functional magnetic resonance imaging (fMRI) has made significant contributions in improving our understanding of the human brain function. However, some limitations of fMRI studies, including those associated with the small sample sizes that are typically employed, raise concerns about validity of the technique. Lately, growing interest has been observed in combining the results of multiple fMRI studies in a meta-analysis. This can potentially address the limitations of single experiments and raise opportunities for reaching safer conclusions. Coordinate-based meta-analyses (CBMA) use the peak activation locations from multiple studies to find areas of consistent activations across experiments. CBMA presents statisticians with many interesting challenges. Several issues have been solved but there are also many open problems. In this thesis, we review literature on the topic and after describing the unsolved problems we then attempt to address some of the most important. The first problem that we approach is the incorporation of study-specific characteristics in the meta-analysis model known as meta-regression. We propose an novel meta-regression model based on log-Gaussian Cox processes and develop a parameter estimation algorithm using the Hamiltonian Monte Carlo method. The second problem that we address is the use of CBMA data as prior in small underpowered fMRI studies. Based on some existing work on the topic, we develop a hierarchical model for fMRI studies that uses previous CBMA findings as a prior for the location of the effects. Finally, we discuss a classical problem of meta-analysis, the file drawer problem, where studies are suppressed from the literature because they fail to report any significant finding. We use truncated models to infer the total number of non-significant studies that are missing from a database. All our methods are tested on both simulated and real data.
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Donegan, Sarah. "The value of individual patient data for mixed treatment comparison meta-analysis." Thesis, University of Liverpool, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.570446.
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Numerous treatments can be compared simultaneously using a single mixed treatment comparison (MTC) meta-analysis model that combines all direct and indirect evidence. Three key assumptions underlie MTC methodology: similarity, consistency, and homogeneity. Meta-analysis can be based on individual patient data (IPD) and/or aggregate data. Acquiring IPD will improve the quality of conventional pair-wise meta-analysis in various ways. The value of IPD for MTC meta-analysis is currently unknown. This thesis explores the benefits of using IPD covariate information to assess the underlying assumptions of MTCs. The methodology is illustrated using real IPD from a single multicentre trial that compared artemisinin-based combination therapies (ACTs) for treating uncomplicated malaria in African children. Existing aggregate data MTC meta-analysis models for dichotomous outcomes are extended to allow for patient-level outcomes and covariates. The potential benefits of IPD are evaluated by comparing results from IPD models including treatment by patient-level covariate interactions, with those from aggregate data models including treatment by study-level covariate interactions. The results showed that treatment effects and drug rankings based on IPD, differed from those estimated using aggregate data. The inclusion of patient-level, rather than site-level covariates, produced more precise treatment effects and regression coefficients for the interactions. Therefore, including patient-level covariates was more favourable than including site-level data. A new approach is proposed to determine whether any existing inconsistency is reduced, or explained, following the inclusion of treatment by covariate interactions in the MTC model. The same approach is followed for models involving study-level covariates and models with patient- level covariates. Using aggregate data, results showed that there were too few sites contributing direct evidence to allow consistency to be established when including treatment by covariate interactions. Based on IPD, the regression coefficients for the interactions were estimated from the within-site and across-site interactions and therefore consistency could be determined. Patient- level covariates, rather than site-level data, were clearly beneficial when judging whether inconsistency was reduced by including treatment by covariate interactions in the model. Novel MTC meta-analysis models for a dichotomous outcome are introduced that each combine IPD and aggregate data using a one-stage approach while including treatment by covariate interactions. The methodology is illustrated using the real IPD and a supplementary dataset consisting of aggregate data from a single Cochrane review that also compared ACTs. When MTC models were fitted to the aggregate dataset alone, the results were imprecise and the Markov chain Monte Carlo chains did not convergence. When MTC models were applied to the IPD and when one-stage models were fitted to all data, convergence of the chains was adequate and the credibility intervals for the treatment effects and regression coefficients were much narrower. When exploring treatment by covariate interactions, it was beneficial to obtain IPD, if only for a subset of trials, and to combine the patient-level data with the additional aggregated data in a me ta-analysis model. This thesis has shown that IPD can be extremely valuable in MTC meta-analysis.
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Lin, Enxuan. "Some new developments in data transformation and meta-analysis with small number of studies." HKBU Institutional Repository, 2019. https://repository.hkbu.edu.hk/etd_oa/636.
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Meta-analysis is an important statistical tool for systematic reviews and evidence-based medicine. Extracting the observed effect sizes, assessing the magnitude of heterogeneity, choosing the suitable statistical model, and interpreting the summary effect size are four key steps in meta-analysis. It is known that each of the above steps has its own unique characteristics and may require some specific attention. As an example, the observed effect sizes from individual studies may not be reported in the same scale and hence cannot be combined directly. Another example is on selecting a model for meta-analysis from the common-effect model and the random-effects model. When a meta-analysis contains only few studies, the common-effect model and the random-effects model will often lead to misleading or unreliable results. In the first part of the thesis, we give a brief introduction on evidence-based medicine, systematic reviews and meta-analysis. We will also show their practical importance, display their relationships, and present a motivating example for conducting a meta-analysis. In Chapter 2, we first review the common effect sizes in meta-analysis for both continuous data and binary data. How to combine different categories of effect sizes is a critical issue after extracting the observed effect sizes from the clinical studies in the literature. For continuous data, researchers have recently proposed methods that transform the five number summary to the sample mean and standard deviation (Hozo et al., 2005; Wan et al., 2014; Luo et al., 2018). For binary data, the transformation from the odds ratio (OR) to the relative risk (RR) in the cohort study was proposed by Zhang and Yu (1998). To the best of our knowledge, however, there is little work in the literature that converts OR to RR in the case-control study. In view of this, we establish a new formula for this transformation to fulfill the gap. The performance of the new method will be examined through simulations and real data analysis. Our method and formulas can not only handle meta-analyses with different effect sizes, but also offer some insights for medical researchers to further understand the meaning of OR and RR in both cohort and case-control studies. In Chapter 3, we first give a brief introduction on the three available models in meta-analysis: the common-effect model, the random-effects model, and the fixed-effects model. When a meta-analysis contains only few studies, the common-effect model and the random-effects model will often lead to misleading or unreliable results. In contrast, the fixed-effects model is capable to provide a good compromise between the existing two models. In this chapter, we propose to further improve the estimation accuracy of the average effect in the fixed-effects model by assigning different weight for each study as well as fully utilizing the information in the within-study variances. Through theory and simulation, we demonstrate that the fixed-effects model can serve as the most convincing model for meta-analysis with few studies. And most importantly, with a total of three models, we expect that meta-analysis can be conducted more flexibly, more meaningfully, and more accurately. In Chapter 4, we first give a brief introduction on the heterogeneity in meta-analysis. We then review the methods for quantifying heterogeneity in three directions as follows: the tests for heterogeneity, the estimates of the between-study variance, and the measures of the impact of heterogeneity. Note that most existing methods were derived under the assumption of known within-study variances. In practice, however, a direct use of the reported within-study variance estimates may largely reduce the power of the tests and also lower the accuracy of the estimates, especially when the sample sizes in some studies are not sufficiently large. To overcome this problem, we propose a family of shrinkage estimators for the within-study variances that are able to borrow information across the studies, and derive the optimal shrinkage parameters under the Stein loss function. We then apply the new estimates of the within-study variances to some well-known methods for measuring heterogeneity. Simulation studies and real data examples show that our shrinkage estimators can dramatically reduce the estimation bias and hence improve the exiting literature. Keywords: Common-effect model, Effect size, Fixed-effects model, Heterogeneity, Meta-analysis, Odds ratio, Random-effects model, Relative risk, Risk ratio
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Koeva, Martina I. "Stemness revisited : a meta analysis of stem cell signatures using high-throughput data integration /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2009. http://uclibs.org/PID/11984.
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Warn, David Edward. "Applications and extensions of Bayesian hierarchical models for meta-analysis of binary outcome data." Thesis, University of Cambridge, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.620461.
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Xiong, Xu. "Anemia during pregnancy and birth outcome: new data from china and a meta-analysis." Doctoral thesis, Universite Libre de Bruxelles, 1996. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/212449.
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Owens, Corina M. "Meta-Analysis of Single-Case Data: A Monte Carlo Investigation of a Three Level Model." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3273.
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Numerous ways to meta-analyze single-case data have been proposed in the literature, however, consensus on the most appropriate method has not been reached. One method that has been proposed involves multilevel modeling. This study used Monte Carlo methods to examine the appropriateness of Van den Noortgate and Onghena's (2008) raw data multilevel modeling approach to the meta-analysis of single-case data. Specifically, the study examined the fixed effects (i.e., the overall average baseline level and the overall average treatment effect) and the variance components (e.g., the between person within study variance in the average baseline level, the between study variance in the overall average baseline level, the between person within study variance in the average treatment effect) in a three level multilevel model (repeated observations nested within individuals nested within studies). More specifically, bias of point estimates, confidence interval coverage rates, and interval widths were examined as a function of specific design and data factors. Factors investigated included (a) number of primary studies per meta-analysis, (b) modal number of participants per primary study, (c) modal series length per primary study, (d) level of autocorrelation, and (3) variances of the error terms. The results of this study suggest that the degree to which the findings of this study are supportive of using Van den Noortgate and Onghena's (2008) raw data multilevel modeling approach to meta-analyzing single-case data depends on the particular effect of interest. Estimates of the fixed effects tended to be unbiased and produced confidence intervals that tended to overcover but came close to the nominal level as level-3 sample size increased. Conversely, estimates of the variance components tended to be biased and the confidence intervals for those estimates were inaccurate.
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Sequeira, Olinda Maria dos Santos. "Sector energético : eficiência, técnicas de fronteiras e meta-análise." Doctoral thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/9109.
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Doutoramento em EconomiaNeste trabalho, através de uma meta-análise, pretende-se integrar os resultados obtidos nos estudos sobre a eficiência, realizados no sector energético, e analisar se as decisões metodológicas influenciam os valores de eficiência estimados. Os dados são constituídos por 162 modelos reportados em 63 artigos científicos que analisaram empiricamente o nível de eficiência no sector energético no período de 1979 a 2013. Através de um modelo de meta- regressão, a investigação focaliza-se em tentar perceber que efeitos podem ter as diferentes especificações dos modelos nos valores estimados para a eficiência. Analisa-se o impacto que as variáveis - revista no qual o estudo é publicado, ano de publicação, método paramétrico versus não paramétrico, tipo de função, forma funcional aplicada, orientação input versus output, distribuição do erro, efeitos aleatórios versus efeitos fixos, dimensão da amostra, tipo de dados, ano a que se referem os dados e número de variáveis output incluídas - podem ter no nível de eficiência estimado para as unidades de produção e distribuição energética. Os resultados parecem demonstrar que o ano de publicação do artigo, opção pela função custo, a forma funcional translog, a distribuição semi-normal para o termo de erro, dados de painel e o número de variáveis output têm um impacto negativo no cálculo da estimativa da eficiência. Por outro lado, a opção pelo modelo de efeitos aleatórios tem um impacto positivo. Relativamente à média dos anos de observação e dimensão da amostra, os resultados demonstram que não existe qualquer efeito relevante. Existe evidência estatística, a um nível de significância de 5%, para afirmar que as variáveis Energy Economics journal, modelos paramétricos, orientação input e rendimentos variáveis à escala produzem efeito positivo na estimativa da eficiência. Por último, o modelo especificado neste trabalho e os resultados obtidos permitem acomodar outras variáveis que tenham como objectivo o aprofundamento e futuros desenvolvimentos deste trabalho.
In this paper, through a meta-analysis, we intend to integrate the results obtained in studies conducted on the efficiency in the energy sector and try to understand if indeed the methodological decisions influence the efficiency values estimated. The data consist of 162 models reported in 63 scientific articles that empirically analyzed the level of efficiency in the energy sector from 1979 to 2013. Through a meta-regression model, the research focuses on trying to understand what effects may have the different specifications of the models in the estimated values for efficiency. We analyze the impact of variables - journal in which the study is published, year of publication, parametric versus nonparametric method, type of function, functional form applied, input versus output orientation, error distribution, random effects versus fixed effects, sample size, data type, the year to which they relate data and number of output variables - can have on the estimated level of efficiency for units of energy production and distribution. The results demonstrate that the year of publication of the article, the option cost function, the translog functional form, the half-normal distribution for the error term, panel data and the number of output variables have a negative impact on the calculation of the estimate value of efficiency. Moreover, the choice of the random effects model has a positive impact. For the average of years of observation and sample size, the results demonstrate that there is no significant effect. There is statistical evidence, a 5% significance level, for asserting that the variables Journal Energy Economics, parametric method, input orientation and variables returns to scale produce positive effect on the estimation of efficiency. Finally the model specified in this study and the results indicate the possibility of integrating other variables that aim to deepen this work and future developments of this work are indicated.
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Zabriskie, Brinley. "Methods for Meta–Analyses of Rare Events, Sparse Data, and Heterogeneity." DigitalCommons@USU, 2019. https://digitalcommons.usu.edu/etd/7491.
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The vast and complex wealth of information available to researchers often leads to a systematic review, which involves a detailed and comprehensive plan and search strategy with the goal of identifying, appraising, and synthesizing all relevant studies on a particular topic. A meta–analysis, conducted ideally as part of a comprehensive systematic review, statistically synthesizes evidence from multiple independent studies to produce one overall conclusion. The increasingly widespread use of meta–analysis has led to growing interest in meta–analytic methods for rare events and sparse data. Conventional approaches tend to perform very poorly in such settings. Recent work in this area has provided options for sparse data, but these are still often hampered when heterogeneity across the available studies differs based on treatment group. Heterogeneity arises when participants in a study are more correlated than participants across studies, often stemming from differences in the administration of the treatment, study design, or measurement of the outcome. We propose several new exact methods that accommodate this common contingency, providing more reliable statistical tests when such patterns on heterogeneity are observed. First, we develop a permutation–based approach that can also be used as a basis for computing exact confidence intervals when estimating the effect size. Second, we extend the permutation–based approach to the network meta–analysis setting. Third, we develop a new exact confidence distribution approach for effect size estimation. We show these new methods perform markedly better than traditional methods when events are rare, and heterogeneity is present.
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Bergeron, Charlene Emma. "Research on Lobster Age-Size Relationships: Developing Regionally Specified Growth Models from Meta-analysis of Existing Data." Fogler Library, University of Maine, 2011. http://www.library.umaine.edu/theses/pdf/BergeronC2011.pdf.
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Raynaut, William. "Perspectives de méta-analyse pour un environnement d'aide à la simulation et prédiction." Thesis, Toulouse 3, 2018. http://www.theses.fr/2018TOU30005/document.
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L'émergence du phénomène Big Data a créé un besoin grandissant en analyse de données, mais, bien souvent, cette analyse est conduite par des experts de différents domaines ayant peu d'expérience en science des données. On s'intéresse donc à ce besoin d'assistance à l'analyse de données, qui commence tout juste à recevoir une certaine attention des communautés scientifiques, donnant naissance au domaine de la méta-analyse. Les premières approches du sujet se révélant souvent similaires et peu abouties, on tente en particulier de permettre de nouvelles approches de méta-analyse pour adresser ce problème d'assistance à l'analyse de données. Pour ce faire, une première étape cruciale est de déterminer ce qu'est une méta-analyse performante, aucun standard n'ayant encore été établi dans ce domaine relativement neuf. On propose ainsi un cadre générique d'évaluation de méta-analyse, permettant de comparer et caractériser finement diverses techniques de méta- analyse. Ensuite, afin d'ouvrir de nouvelles voies, on s'intéresse à un verrou majeur de la méta-analyse : la caractérisation de jeu de données. On propose et évalue alors une caractérisation par dissimilarité faisant usage de toute l'information disponible pour autoriser de nouvelles approches de méta-analyse. L'utilisation de cette caractérisation par dissimilarité permettant de recommander facilement des processus d'analyse de données complets, on décrit enfin les nouvelles approches de méta-analyses rendues possibles, ainsi que les processus afférents d'assistance à l'analyse de donnéesThe emergence of the big data phenomenon has led to increasing demands in data analysis, which most often are conducted by other domains experts with little experience in data science. We then consider this important demand in intelligent assistance to data analysis, which receives an increasing attention from the scientific community. The first takes on the subject often possessing similar shortcomings, we propose to address it through new processes of meta-analysis. No evaluation standard having yet been set in this relatively new domain, we first propose a meta-analysis evaluation framework that will allow us to test and compare the developed methods. In order to open new approaches of meta-analysis, we then consider one of its recurring issue: dataset characterization. We then propose and evaluate such a characterization, consisting in a dissimilarity between datasets making use of a precise topological description to compare them. This dissimilarity allows a new meta-analysis approach producing recommendations of complete data analysis processes, which we then evaluate on a proof of concept. We thus detail the proposed methods of meta-analysis, and the associated process of assistance to data analysis
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Enders, Dirk, Monika Balzer-Geldsetzer, Oliver Riedel, Richard Dodel, Hans-Ulrich Wittchen, Sven-Christian Sensken, Björn Wolff, and Jens-Peter Reese. "Prevalence, Duration and Severity of Parkinson’s Disease in Germany: A Combined Meta-Analysis from Literature Data and Outpatient Samples." Karger, 2017. https://tud.qucosa.de/id/qucosa%3A70623.
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Background: Epidemiological data on the prevalence of Parkinson’s disease (PD) in Germany are limited. The aims of this study were to estimate the age- and gender-specific prevalence of PD in Germany as well as the severity and illness duration. Summary: A systematic literature search was performed in 5 different databases. European studies were included if they reported age- and gender-specific numbers of prevalence rates of PD. Meta-analytic approaches were applied to derive age- and gender-specific pooled prevalence estimates. Data of 4 German outpatient samples were incorporated to calculate the proportion of patients with PD in Germany grouped by Hoehn and Yahr (HY) stages and disease duration. In the German population, 178,169 cases of PD were estimated (prevalence: 217.22/100,000). The estimated relative illness duration was 40% with less than 5 years, 31% with 5–9 years, and 29% with more than 9 years. The proportions for different HY stages were estimated at 13% (I), 30% (II), 35% (III), 17% (IV), and 4% (V), respectively. Key Message: We provide an up-to-date estimation of age and gender-specific as well as severity-based prevalence figures for PD in Germany. Further community studies are needed to estimate population-based severity distributions and distributions of non-motor symptoms in PD.
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Kosch, Robin [Verfasser], Klaus [Akademischer Betreuer] Jung, Stefanie [Akademischer Betreuer] Becker, and Martin [Akademischer Betreuer] Eisenacher. "Bioinformatical Meta-Analysis of High-Throughput Expression Data from Neuroinfection Research / Robin Kosch, ; Klaus Jung, Stefanie Becker, Martin Eisenacher." Hannover : Stiftung Tierärztliche Hochschule Hannover, 2019. http://d-nb.info/1191752747/34.
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Lozada, Can Claudia Eli. "Issues in meta-analysis of binary data when using the log odds ratio as a measure of treatment effect." Thesis, University of Warwick, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439610.
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Wang, Shuo. "An Improved Meta-analysis for Analyzing Cylindrical-type Time Series Data with Applications to Forecasting Problem in Environmental Study." Digital WPI, 2015. https://digitalcommons.wpi.edu/etd-theses/386.
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This thesis provides a case study on how the wind direction plays an important role in the amount of rainfall, in the village of Somi$acute{o}$. The primary goal is to illustrate how a meta-analysis, together with circular data analytic methods, helps in analyzing certain environmental issues. The existing GLS meta-analysis combines the merits of usual meta-analysis that yields a better precision and also accounts for covariance among coefficients. But, it is quite limited since information about the covariance among coefficients is not utilized. Hence, in my proposed meta-analysis, I take the correlations between adjacent studies into account when employing the GLS meta-analysis. Besides, I also fit a time series linear-circular regression as a comparable model. By comparing the confidence intervals of parameter estimates, covariance matrix, AIC, BIC and p-values, I discuss an improvement on the GLS meta analysis model in its application to forecasting problem in Environmental study.
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Treakle, Jesse W. "Moving from Fear towards Unity among Intergroup Dialogue Participants in Israel-Palestine: Findings from a Qualitative Meta-Data-Analysis." NSUWorks, 2017. http://nsuworks.nova.edu/shss_dcar_etd/67.
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This qualitative meta-data-analysis was designed to identify themes of experience of Israeli Jewish and Palestinian Arab intergroup dialogue participants. A review of the literature indicated a scarcity of research that describes the ‘meaning-making’ processes that these participants undergo while engaged in structured intergroup dialogue, and this study was designed to address that shortage. The analyst conducted a targeted search of academic journal articles and Ph.D. dissertations published after 1999. The result of this search was a set of 17 primary reports, and the findings of this study are based on the verbatim quotations of Israeli Jewish and Palestinian Arab intergroup dialogue participants as cited within the set of primary reports. The analyst performed a thematic analysis of said quotations and, guided by contact theory, social identity theory, and intersubjectivity theory, concluded that Israeli Jews, Palestinian Arab citizens of Israel, and Palestinian Arabs in the Occupied Territories all enter dialogue carrying varying levels of fear and anger; and if they remain dedicated to dialogue processes, they eventually—to varying degrees—seek truth, pursue justice, and realize unity. This study’s primary contribution is its explication of the specific areas intergroup dialogue facilitators and researchers need to focus in Israel-Palestine. The findings indicate that more research needs to be conducted on inter-religious, narrative, and activist models. Furthermore, the data evidences the presence of geotheological influences on participant perspectives. Overall, the findings of this dissertation are consistent with previous research that affirms the power of dominant group narratives to sustain intractable conflict and the necessity of intergroup dialogue to foster cross-group friendships that can overcome intractable conflict.
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ZHONG, WEI. "STATISTICAL APPROACHES TO ANALYZE CENSORED DATA WITH MULTIPLE DETECTION LIMITS." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1130204124.
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Maalouf, George. "A study of AODV and DSR protocols : A meta-analysis of AODV and DSR protocols." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-27970.
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There is a big number of people dying every year from car accidents and not solving this problem is a big issue. Communication protocols have been created in mobile ad-hoc network (MANET) to be able to solve this issue. AODV and DSR are two protocols that are used in this communication. The fact that there is mobile nodes makes it hard to keep track of the efficiency of this communication. This study has for objective giving a better understanding as to which protocol performs better and answering four important questions to know to be able to evaluate what protocol is better according to those parameters or criteria. The implemented method to solve this problem is through a meta-analysis and this meta-analysis is done through a qualitative research, literature review for critical literature reading and data collection to select the appropriate studies and exclud- ing the irrelevant studies based on other criteria. The evaluation of these param- eters are based on others’ work and reading the work from critical eyes. This study compares AODV and DSR from the criteria that are chosen. The study has a critical analysis of the results collected through the different papers show that AODV has outperformed DSR in most of the cases and answering the proposed questions in the study. Finally concluding that AODV is more effective in the case of high congestion compared to DSR but making a bit hard to have a clear cut answer when it comes to the criteria but AODV performed better in all the cases in high congestion.
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Hepburn, Joseph Christophe. "Evaluating spatial and temporal variability in British Columbia human palaeodiet : a meta-analysis of existing and new stable isotope data." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/57768.
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This study presents a meta-analysis of all available archaeological human carbon and nitrogen stable isotope data from British Columbia (BC). Overall, isotope signatures for the coast demonstrate a heavy marine specialization consistent with archaeological and ethnographic reconstructions of Northwest Coast diet. Within this marine specialization, the data for coastal BC demonstrate a high degree of regional dietary variability, although high trophic level marine prey species are of ubiquitous importance. No large-scale dietary shifts are present for the coast, with consistent carbon and nitrogen δ-values across the entire timespan represented. Notable outliers exist throughout the coast, with three individuals possessing fully terrestrial diets in regions with otherwise heavily marine diets. In the BC interior diets are much more variable, representing a range between purely terrestrial to mixed marine (anadromous fish) and terrestrial. Along salmon-bearing rivers, the apparent marine component of diet is positively correlated with downstream proximity to the ocean.Arts, Faculty of
Anthropology, Department of
Graduate
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Malthaner, Richard Adam. "A comparison of a meta-analysis of the literature and a mega-analysis of individual patient data for preoperative chemotherapy for carcinoma of the esophagus." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ39852.pdf.
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Hosseini, S. (Seyedrebvar). "Data selection for cross-project defect prediction." Doctoral thesis, Oulun yliopisto, 2019. http://urn.fi/urn:isbn:9789526224480.
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Abstract Context: This study contributes to the understanding of the current state of cross-project defect prediction (CPDP) by investigating the topic in themes, with special focus on data approaches and covering search-based training data selection, by proposing data selection methods and investigating their impact. The empirical evidence for this work is collected through a formal systematic literature review method for the review, and from experiments on open source projects. Objective: We aim to understand and summarize the manner in which various data manipulation approaches are used in CPDP and their potential impacts on performance. Further, we aim at utilizing search-based methods to produce evolving training data sets to filter irrelevant instances from other projects before training. Method: Through a series of studies following the literature review of current state of CPDP, we propose a search-based method called genetic instance selection (GIS). We validate our initial findings by conducting the next study on a large set of data sets with multiple feature sets. We refine our design decisions using an exploratory study. Finally, we investigate an existing meta-learning approach, provide insights on its design and propose an alternative iterative data selection method. Results: The literature review reveals lower performances of CPDP in comparison with within project defect prediction (WPDP) models and provides a set of primary studies to be used as the basis for future research. Our proposed data selection methods make the case for search-based approaches considering their higher effectiveness and performance. We identified potential impacting factors on the effectiveness through the exploratory study and proposed methods to create better CPDP models. Conclusions: The proposal of numerous approaches in the literature over the last decade has led to progress in the area and the acquired knowledge and tools apply to many similar domains and can act as parts of academic curricula as well. Future directions of study can include searching for better validation data, better feature selection techniques, tuning the parameters of the search-based models, tuning hyper-parameters of learners, investigating the effects of multiple sources of optimization (learner, instances and features) and the impact of the class imbalance problemTiivistelmä Tausta: Tämä tutkimus edistää projektienvälisten virheiden ennustamisen nykytilan ymmärtämistä (CPDP) tutkimalla aihetta teemoissa, keskittyen erityisesti tiedollisiin lähestymistapoihin ja hakuperusteisen harjoitusdatan valintaan esittelemällä datan valintamenetelmiä ja tutkimalla niiden vaikutuksia. Tämän työn empiirinen todistusaineisto on koottu muodollisella systemaattisella kirjallisuuskatsauksella ja avoimen lähdekoodin projekteissa tehdyillä kokeilla. Tavoite: Pyrimme ymmärtämään ja tiivistämään tavan, jolla erilaisia datan käsittelyn lähestymistapoja käytetään CPDP:ssa sekä niiden potentiaalisia vaikutuksia suorituskykyyn. Lisäksi, tavoitteenamme on hyödyntää hakuperusteisia menetelmiä muodostamaan kehittyviä harjoitusdata-settejä suodattamaan epäolennaisia esiintymiä muista projekteista ennen koulutusta. Menetelmä: CPDP:n nykytilan kirjallisuuskatsauksen jälkeen tehtyjen tutkimusten avulla ehdotamme hakuperusteista menetelmää, jota kutsutaan geneettisen esiintymän valinnaksi (GIS). Todistamme alustavat havaintomme suorittamalla seuraavan tutkimuksen suurella joukolla datasettejä, joilla on useita ominaisuuksia. Jalostamme suunnittelupäätöksiämme käyttäen tutkivaa tutkimusta. Lopuksi, tutkimme vallitsevaa meta-oppimisen lähestymistapaa ja tarjoamme näkemyksiä sen suunnitteluun ja ehdotamme vaihtoehtoista, toistuvaa datan valintamenetelmää. Tulokset: Kirjallisuuskatsaus paljastaa CPDP:n heikomman suorituskyvyn verrattuna projektinsisäisten virheiden ennustamisen (WPDP) malleihin ja tarjoaa joukon primaaritutkimuksia, joita voidaan käyttää perustana myöhemmälle tutkimukselle. Ehdottamamme datan valintamenetelmät puoltavat hakuperusteisten menetelmiä niiden paremman tehokkuuden ja suorituskyvyn vuoksi. Tunnistimme potentiaalisia tehokuuteen vaikuttavia tekijöitä tutkivien tutkimusten avulla ja ehdotimme metodeja parempien CPDP mallien luomiseksi. Johtopäätökset: Viime vuosikymmenten aikana kirjallisuudessa esitellyt lukuisat menetelmät ovat edistäneet alaa ja hankittu tieto ja työkalut soveltuvat monille samanlaisille alueille ja voivat toimia myös osana akateemisia opetussuunnitelmia. Tutkimuksen tulevat linjaukset voivat sisältää validointiin paremmin soveltuvan datan haun, paremmat ominaisuuksien valintatekniikat, hakuperusteisten mallien parametrien hienosäädön, oppijoiden hyper-parametrien hienosäädön, tutkimuksen useiden optimoinnin lähteiden vaikutuksista (oppija, esiintymät, ominaisuudet) ja luokan epätasapaino-ongelman vaikutuksesta
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Stringer, Henri A. "An examination of data supporting hypothesized mediational pathways underlying the relationship between mental imagery and motor skill performance, a meta-analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ61399.pdf.
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Friedrich, Torben. "New statistical Methods of Genome-Scale Data Analysis in Life Science - Applications to enterobacterial Diagnostics, Meta-Analysis of Arabidopsis thaliana Gene Expression and functional Sequence Annotation." kostenfrei, 2009. http://www.opus-bayern.de/uni-wuerzburg/volltexte/2009/3985/.
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Odani, Motoi. "A Bayesian meta-analytic approach for safety signal detection in randomized clinical trials." 京都大学 (Kyoto University), 2017. http://hdl.handle.net/2433/225514.
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Pietschmann, Sophie, Bueren André O. von, Michael J. Kerber, Brigitta G. Baumert, Rolf-Dieter Kortmann, and Klaus Müller. "An individual patient data meta-analysis on characteristics, treatments and outcomes of Glioblastoma/ Gliosarcoma patients with metastases outside of the central nervous system." Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-169939.
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Dheri, Aman. "Distributed Network Meta-Analysis Estimates Results from Individual-Level Analysis Using Ontario Health Administrative Data on Pediatric Inflammatory Bowel Disease Health Services Use: A Population-Based Cohort Study." Thesis, Université d'Ottawa / University of Ottawa, 2020. http://hdl.handle.net/10393/40720.
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Over the last couple of decades changes to pediatric inflammatory bowel disease (IBD) care may have altered health services use among these children. I used a retrospective matched cohort design and population-based health administrative data to first quantify trends in IBD health services and surgical outcomes in Ontario IBD children diagnosed between 1994-2012. I then used these results to validate the distributed network analysis method – a method being increasingly used in Canadian multi-province studies where privacy regulations prevent sharing of individual-level data across provincial borders - using Ontario’s Local Health Integration Networks. I found (1) decreasing hospitalizations and surgical outcomes but increasing outpatient visit rates, suggesting changing patterns of health care use in Ontario children with IBD, and, (2) distributed network analyses is a satisfactory privacy-preserving alternative to individual-level analysis under the conditions tested in my study, providing a tested analysis method for researchers using multi-jurisdictional data.
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Lo, Chih-Chung. "Using effect size in information fusion for identifying object presence and object quality /." free to MU campus, to others for purchase, 1996. http://wwwlib.umi.com/cr/mo/fullcit?p9823330.
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Fallah-Fini, Saeideh. "Measuring the Efficiency of Highway Maintenance Operations: Environmental and Dynamic Considerations." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/77284.
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Highly deteriorated U.S. road infrastructure, major budgetary restrictions and the significant growth in traffic have led to an emerging need for improving efficiency and effectiveness of highway maintenance practices that preserve the road infrastructure so as to better support society's needs. Effectiveness and efficiency are relative terms in which the performance of a production unit or decision making unit (DMU) is compared with a benchmark (best practice). Constructing the benchmark requires making a choice between an "estimation approach" based on observed best practices (i.e., using data from input and output variables corresponding to observed production units (DMUs) to estimate the benchmark with no elaboration on the details of the production process inside the black box) or an "engineering approach" to find the superior blueprint (i.e., focusing on the transformation process inside the black box for a better understanding of the sources of inefficiencies). This research discusses: (i) the application of the estimation approach (non-parametric approach) for evaluating and comparing the performance of different highway maintenance contracting strategies (performance-based contracting versus traditional contracting) and proposes a five-stage meta-frontier and bootstrapping analytical approach to account for the heterogeneity in the DMUs, the resulting bias in the estimated efficiency scores, and the effect of uncontrollable variables; (ii) the application of the engineering approach by developing a dynamic micro-level simulation model for the highway deterioration and renewal processes and its coupling with calibration and optimization to find optimum maintenance policies that can be used as a benchmark for evaluating performance of road authorities.
This research also recognizes and discusses the fact that utilization of the maintenance budget and treatments that are performed in a road section in a specific year directly affect the road condition and required maintenance operations in consecutive years. Given this dynamic nature of highway maintenance operations, any "static" efficiency measurement framework that ignores the inter-temporal effects of inputs and managerial decisions in future streams of outputs (i.e., future road conditions) is likely to be inaccurate. This research discusses the importance of developing a dynamic performance measurement framework that takes into account the time interdependence between the input utilization and output realization of a road authority in consecutive periods.
Finally, this research provides an overview of the most relevant studies in the literature with respect to evaluating dynamic performance and proposes a classification taxonomy for dynamic performance measurement frameworks according to five issues. These issues account for major sources of the inter-temporal dependence between input and output levels over different time periods and include the following: (i) material and information delays; (ii) inventories; (iii) capital or generally quasi-fixed factors and the related topic of embodied technological change; (iv) adjustment costs; and (v) incremental improvement and learning models (disembodied technological change).
In the long-term, this line of research could contribute to a more efficient use of societal resources, greater level of maintenance services, and a highway and roadway system that is not only safe and reliable, but also efficient.Ph. D.
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Magidin, de Kramer Raquel. "Evaluation of Cross-Survey Research Methods for the Estimation of Low-Incidence Populations." Thesis, Boston College, 2016. http://hdl.handle.net/2345/bc-ir:107241.
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Thesis advisor: Henry BraunThis study evaluates the accuracy, precision, and stability of three different methods of cross-survey analysis in order to determine their suitability for estimating the proportions of low-incidence populations. Population parameters of size and demographic distribution are necessary for planning and policy development. The estimation of these parameters for low-incidence populations poses a number of methodological challenges. Cross-survey analysis methodologies offer an alternative to generate useful, low-incidence population estimates not readily available in today's census without conducting targeted, costly surveys to estimate group size directly. The cross-survey methods evaluated in the study are meta-analysis of complex surveys (MACS), pooled design-based cross-survey (PDCS), and Bayesian multilevel regression with post-stratification (BMRP). The accuracy and precision of these methods were assessed by comparing the estimates of the proportion of the adult Jewish population in Canada generated by each method with benchmark estimates. The stability of the estimates, in turn, was determined by cross-validating estimates obtained with data from two random stratified subsamples drawn from a large pool of US surveys. The findings of the study indicate that, under the right conditions, cross-survey methods have the potential to produce very accurate and precise estimates of low-incidence populations. The study did find that the level of accuracy and precision of these estimates varied depending on the cross-survey method used and on the conditions under which the estimates were produced. The estimates obtained with PDCS and BMRP methodologies were more accurate than the ones generated by the MACS approach. The BMRP approach generated the most accurate estimates. The pooled design-based cross-survey method generated relatively accurate estimates across all the scenarios included in the study. The precision of the estimates was found to be related to the number of surveys considered in the analyses. Overall, the findings clearly show that cross-survey analysis methods provide a useful alternative for estimation of low-incidence populations. More research is needed to fully understand the factors that affect the accuracy and precision of estimates generated by these cross-survey methods
Thesis (PhD) — Boston College, 2016
Submitted to: Boston College. Lynch School of Education
Discipline: Educational Research, Measurement and Evaluation
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Van, der Walt Christiaan Maarten. "Data measures that characterise classification problems." Diss., Pretoria : [s.n.], 2008. http://upetd.up.ac.za/thesis/available/etd-08292008-162648/.
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Moffa, Adriano Henrique de Matos. "Estimulação transcraniana por corrente continua na fase aguda do episódio depressivo maior: uma meta-análise de dados individuais." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/47/47135/tde-07102016-180727/.
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Introdução: A Estimulação Transcraniana por Corrente Contínua (ETCC) é uma intervenção não farmacológica com resultados discordantes quanto à sua eficácia para o tratamento do Episódio Depressivo Maior (EDM). Possivelmente devido a heterogeneidade dos estudos, as três meta-análises publicadas até agora sobre o assunto apontam para uma pequena vantagem a favor da técnica, dependendo da variável de desfecho analisada (melhora de depressão ou resposta). Todas essas meta-análises utilizaram dados agregados. Focamo-nos, no presente estudo, na realização de uma revisão sistemática da literatura e de uma meta-análise baseada em dados individuais de pacientes (MA-DIP) com Depressão Maior (DM) submetidos à ETCC na fase aguda. Este tipo de análise é mais preciso na avaliação da eficácia de uma intervenção e na obtenção dos preditores de respostas de tratamento, já que as características individuais de cada sujeito são consideradas ao invés das médias e frequências, como nas meta-análises de dados agregados. Objetivos: (1) avaliar a eficácia da ETCC na fase aguda da DM, (2) identificar preditores de resposta, remissão e melhora da depressão específicos e (3) avaliar a aceitabilidade da intervenção. Resultados: Os dados foram colecionados de 6 ensaios clínicos randomizados placebo controlados, totalizando 289 sujeitos. A ETCC ativa foi estatisticamente superior à estimulação simulada em relação à resposta (34% vs. 19%, respectivamente; RC=2,44, IC 95% = 1,38-4,32, NNT=7), remissão (23,1% vs. 12,7%, respectivamente; RC= 2,38, IC 95% = 1,22 - 4,64, NNT=9) e melhora da depressão (coeficiente = 0,35, IC 95% =0,12 0,57). Demonstrou-se que após ajustes para outros preditores e confundidores, depressão resistente a tratamento e doses mais altas de ETCC foram, respectivamente, inversa e diretamente associadas com a eficácia da ETCC. Conclusões: O tamanho de efeito do tratamento com ETCC foi comparável àqueles reportados, em outros estudos, para a Estimulação Magnética Transcraniana repetitiva (EMTr) e para o tratamento farmacológico (com antidepressivos tricíclicos e inibidores seletivos de recaptação de serotonina) na atenção primária para depressão. Os parâmetros mais importantes para otimização em ensaios clínicos futuros são a refratariedade da depressão e a dose da ETCCIntroduction: Transcranial direct current stimulation (tDCS) is a nonpharmacological intervention for depression. Randomised, sham-controlled clinical trials (RCTs) conducted hitherto have presented mixed results regarding its efficacy. Although recent meta-analyses suggest some efficacy when measuring depression symptoms using a continuous outcome, these meta-analyses were limited in their results as they used an aggregate data approach. We aimed therefore to perform an individual patient data (IPD) meta-analysis. In contrast to an aggregate data meta-analysis, an IPD approach uses the raw data of each participant within a study. IPD is more accurate in estimating the efficacy of an intervention since aggregate data meta-analyses present only summary estimates of efficacy. IPD meta-analysis is also superior to the aggregate data approach for obtaining predictors of treatment outcome, as the characteristics of each patient are assessed instead of the mean and frequency values obtained in the traditional aggregate data meta-analysis. Objectives (a) To provide precise estimates of tDCS efficacy based on continuous (depression improvement) and categorical (response and remission rates) outcomes, (b) to identify variables associated with tDCS efficacy and (c) to estimate the treatment acceptability. Results: Data were gathered from six randomised sham-controlled trials, enrolling 289 patients. Active tDCS was significantly superior to sham for response (34% v. 19%, respectively, odds ratio (OR) = 2.44, 95% CI 1.384.32, number needed to treat (NNT) = 7), remission (23.1% v. 12.7%, respectively, OR = 2.38, 95% CI 1.224.64, NNT = 9) and depression improvement ( coefficient 0.35, 95% CI 0.120.57). Mixed effects models showed that, after adjustment for other predictors and confounders, treatment-resistant depression and higher tDCS doses were, respectively, negatively and positively associated with tDCS efficacy. Conclusions: The effect size of tDCS treatment was comparable with those reported for repetitive transcranial magnetic stimulation (rTMS) and antidepressant drug treatment in primary care. The most important parameters for optimisation in future trials are depression refractoriness and tDCS dose
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Burgess, Stephen. "Statistical issues in Mendelian randomization : use of genetic instrumental variables for assessing causal associations." Thesis, University of Cambridge, 2012. https://www.repository.cam.ac.uk/handle/1810/242184.
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Mendelian randomization is an epidemiological method for using genetic variationto estimate the causal effect of the change in a modifiable phenotype onan outcome from observational data. A genetic variant satisfying the assumptionsof an instrumental variable for the phenotype of interest can be usedto divide a population into subgroups which differ systematically only in thephenotype. This gives a causal estimate which is asymptotically free of biasfrom confounding and reverse causation. However, the variance of the causalestimate is large compared to traditional regression methods, requiring largeamounts of data and necessitating methods for efficient data synthesis. Additionally,if the association between the genetic variant and the phenotype is notstrong, then the causal estimates will be biased due to the “weak instrument”in finite samples in the direction of the observational association. This biasmay convince a researcher that an observed association is causal. If the causalparameter estimated is an odds ratio, then the parameter of association willdiffer depending on whether viewed as a population-averaged causal effect ora personal causal effect conditional on covariates. We introduce a Bayesian framework for instrumental variable analysis, whichis less susceptible to weak instrument bias than traditional two-stage methods,has correct coverage with weak instruments, and is able to efficiently combinegene–phenotype–outcome data from multiple heterogeneous sources. Methodsfor imputing missing genetic data are developed, allowing multiple genetic variantsto be used without reduction in sample size. We focus on the question ofa binary outcome, illustrating how the collapsing of the odds ratio over heterogeneousstrata in the population means that the two-stage and the Bayesianmethods estimate a population-averaged marginal causal effect similar to thatestimated by a randomized trial, but which typically differs from the conditionaleffect estimated by standard regression methods. We show how thesemethods can be adjusted to give an estimate closer to the conditional effect. We apply the methods and techniques discussed to data on the causal effect ofC-reactive protein on fibrinogen and coronary heart disease, concluding withan overall estimate of causal association based on the totality of available datafrom 42 studies.
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Kim, Jaewon. "Trade, Unemployment and Labour Market Institutions." Doctoral thesis, Stockholms universitet, Nationalekonomiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-56464.
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The thesis consists of three papers, summarized as follows. "The Determinants of Labour Market Institutions: A Panel Data Study" This paper analyses the argument that labour market institutions can be thought of as devices for social insurance. It investigates the hypotheses that a country's exposure to external risk and ethnic fractionalisation are correlated with labor market institutions. Extreme bounds analysis with panel data of fourty years indicates that countries that are more open to international trade have stricter employment protection, strong unions, and a more coordinated wage bargaining process. Moreover, there is evidence that union density is negatively associated with the degree of ethnic fracationalisation. "Why do Some Studies Show that Generous Unemployment Benefits Increase Unemployment Rates? A Meta-Analysis of Cross-Country Studies" This paper investigates the hypothesis that generous unemployment benefits give rise to high levels of unemployment by systematically reviewing 34 cross-country studies. In contrast to conventional literature surveys, I perform a meta-analysis which applies regression techniques to a set of results taken from the existing literature. The main finding is that the choice of the primary data and estimation method matter for the final outcome. The control variables in the primary studies also affect the results. "The Effects of Trade on Unemployment: Evidence from 20 OECD countries" This study empirically investigates if international trade has an impact on aggregate unemployment in the presence of labour market institutions. Using data for twenty OECD countries for the years 1961-2008, this study finds that an increase in trade leads to higher aggregate unemployment as it interacts with rigid labour market institutions, whereas it may reduce aggregate unemployment if the labour market is characterised by flexibility. In a country with the average degree of the labour market rigidities, an increase in trade has no significant effect on unemployment rates.
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Keller, Theresa [Verfasser]. "The prevalence sex-shift in single disease and multimorbid asthma and rhinitis during puberty: an individual participant data meta-analysis of European birth cohorts / Theresa Keller." Berlin : Medizinische Fakultät Charité - Universitätsmedizin Berlin, 2018. http://d-nb.info/1170876374/34.
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Horn, Hannes [Verfasser], Humeida Ute Gutachter] Hentschel, Markus [Gutachter] [Riederer, Mitja N. P. [Gutachter] Remus-Emsermann, and Alexander [Gutachter] Keller. "Analysis and interpretation of (meta-)genomic data from host-associated microorganisms / Hannes Horn ; Gutachter: Ute Hentschel Humeida, Markus Riederer, Mitja N. P. Remus-Emsermann, Alexander Keller." Würzburg : Universität Würzburg, 2017. http://d-nb.info/1139641360/34.
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Meddis, Alessandra. "Inference and validation of prognostic marker for correlated survival data with application to cancer." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASR005.
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Les données de survie en grappes sont souvent recueillies dans le cadre de la recherche médicale. Elles sont caractérisées par des corrélations entre des observations appartenant à un même groupe. Ici, nous discutons des extensions a des données en grappes dans différents contextes : évaluation de la performance d'un biomarqueur candidat, et l’estimation de l'effet du traitement dans une méta-analyse sur données individuels (IPD) avec risques concurrents. La première a été motivée par l'étude IMENEO, une méta-analyse où l'intérêt portait sur la validité pronostique des cellules tumorales circulantes (CTCs). Notre objectif était de déterminer dans quelle mesure les CTCs discriminent les patients qui sont morts de ceux qui ne l'ont pas fait dans les t-années, en comparant des individus ayant le même stade de tumeur. Bien que la courbe ROC dépendante du temps ait été largement utilisée pour la discrimination des biomarqueurs, il n'existe pas de méthodologie permettant de traiter des données en grappes censurées. Nous proposons un estimateur pour les courbes ROC dépendantes du temps et pour l'AUC lorsque les temps d'évènements sont correlés. Nous avons employé un modèle de fragilité partagée pour modéliser l'effet des covariables et du biomarqueur sur la réponse afin de tenir compte de l'effet de la grappe. Une étude de simulation a été réalisée et a montré un biais négligeable pour l'estimateur proposé et pour un estimateur non paramétrique fondé sur la pondération par la probabilité inverse d’être censuré (IPCW), tandis qu'un estimateur semi-paramétrique, ignorant la structure en grappe est nettement biaisé.Nous avons également considéré une méta-analyse IPD pour quantifier le bénéfice de l'ajout de la chimiothérapie à la radiothérapie sur chaque risque concurrent pour les patients avec un carcinome nasopharyngien . Les recommandations pour l'analyse des risques concurrents dans le cadre d'essais cliniques randomisés sont bien établies. Étonnamment, aucune recommendation n'a encore été proposée pour l’anlayse d'une méta-analyse IPD avec les risque concurrents. Pour combler cette lacune, ce travail a détaillé la manière de traiter l'hétérogénéité entre les essais par un modèle de régression stratifié pour les risques concurrents et il souligne que les mesures standardes d'hétérogénéité pour évaluer l'incohérence peuvent facilement être utilisées. Les problèmes typiques qui se posent avec les méta-analyses et les avantages dus à la disponibilité des caractéristiques au niveau du patient ont été soulignées. Nous avons proposé une approche landmark pour la fonction d'incidence cumulée afin d'étudier l'impact du temps de suivi sur l'effet du traitement.L'hypothèse d'une taille de grappe non informative était faite dans les deux analyses. On dit que la taille de grappe est informative lorsque la variable réponse dépend de la taille de grappe conditionnellement à un ensemble de variables explicatives. Intuitivement, une méta-analyse répondrait à cette hypothèse. Cependant, la taille de grappe non informative est généralement supposée, même si elle peut être fausse dans certaines situations, ce qui conduit à des résultats incorrects. La taille des grappes informatives (ICS) est un problème difficile et sa présence a un impact sur le choix de la méthodologie. Nous avons discuté plus en détail de l'interprétation des résultats et des quantités qui peuvent être estimées et dans quelles conditions. Nous avons proposé un test pour l'ICS avec des données en grappes censurées. À notre connaissance, il s'agit du premier test sur le contexte de l'analyse de survie. Une étude de simulation a été réalisée pour évaluer la puissance du test et quelques exemples sont fournis à titre d'illustration.L'implémentation de chacun de ces développements est disponible sur https://github.com/AMeddisClustered data often arises in medical research. These are characterized by correlations between observations belonging to the same cluster. Here, we discuss some extension to clustered data in different contexts: evaluating the performance of a candidate biomarker, and assessing the treatment effect in an individual patient data (IPD) meta-analysis with competing risks. The former was motivated by the IMENEO study, an IPD meta-analysis where the prognostic validity of the Circulating Tumor Cells (CTCs) was of interest. Our objective was to determine how well CTCs discriminates patients that died from the one that did not within the t-years, comparing individuals with same tumor stage. Although the covariate-specific time dependent ROC curve has been widely used for biomarker's discrimination, there is no methodology that can handle clusteres censored data. We proposed an estimator for the covariate-specific time dependent ROC curves and area under the ROC curve when clustered failure times are detected. We considered a shared frailty model for modeling the effect of the covariates and the biomarker on the outcome in order to account for the cluster effect. A simulation study was conducted and it showed negligible bias for the proposed estimator and a nonparametric one based on inverse probability censoring weighting, while a semiparametric estimator, ignoring the clustering, is markedly biased.We further considered an IPD meta-analysis with competing risks to assess the benefit of the addition of chemotherapy to radiotherapy on each competing endpoint for patients with nasopharyngeal carcinoma. Recommendations for the analysis of competing risks in the context of randomized clinical trials are well established. Surprisingly, no formal guidelines have been yet proposed to conduct an IPD meta-analysis with competing risk endpoints. To fill this gap, this work detailed: how to handle the heterogeneity between trials via a stratified regression model for competing risks and it highlights that the usual metrics of inconsistency to assess heterogeneity can readily be employed. The typical issues that arise with meta-analyses and the advantages due to the availability of patient-level characteristics were underlined. We proposed a landmark approach for the cumulative incidence function to investigate the impact of follow up on the treatment effect.The assumption of non informative cluster size was made in both the analyses. The cluster size is said to be informative when the outcome depends on the size of the cluster conditional on a set of covariates. Intuitively, a meta-analysis would meet this assumption. However, non informative cluster size is commonly assumed even though it may be not true in some situations and it leads to incorrect results. Informative cluster size (ICS) is a challenging problem and its presence has an impact on the choice of the correct methodology. We discussed more in details interpretation of results and which quantities can be estimated under which conditions. We proposed a test for ICS with censored clustered data. To our knowledge, this is the first test on the context of survival analysis. A simulation study was conducted to assess the power of the test and some illustrative examples were provided.The implementation of each of these developments are available at https://github.com/AMeddis
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Martins, Camila Bertini. "Metanálise caso a caso sob a perspectiva bayesiana." Universidade de São Paulo, 2013. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-10122013-190238/.
Full textAbstract:
O papel da metanálise de sumarizar estudos publicados de mesmo objetivo, por meio da estatística, torna-se cada dia mais fundamental em razão do avanço da ciência e do desejo de usar o menor número de seres humanos em ensaios clínicos, desnecessários, em vários casos. A síntese das informações disponíveis facilita o entendimento e possibilita conclusões robustas. O aumento de estudos clínicos, por exemplo, promove um crescimento da necessidade de metanálises, fazendo com que seja necessário o desenvolvimento de técnicas sofisticadas. Desse modo, o objetivo deste trabalho foi propor uma metodologia bayesiana para a realização de metanálises. O procedimento proposto consiste na mistura das distribuições a posteriori do parâmetro de interesse de cada estudo pertencente à metanálise; ou seja, a medida metanalítica proposta foi uma distribuição de probabilidade e não uma simples medida-resumo. A metodologia apresentada pode ser utilizada com qualquer distribuição a priori e qualquer função de verossimilhança. O cálculo da medida metanalítica pode ser utilizado, desde problemas simples até os mais sofisticados. Neste trabalho, foram apresentados exemplos envolvendo diferentes distribuições de probabilidade e dados de sobrevivência. Em casos, em que se há uma estatística suficiente disponível para o parâmetro em questão, a distribuição de probabilidade a posteriori depende dos dados apenas por meio dessa estatística e, assim, em muitos casos, há a redução de dimensão sem perda de informação. Para alguns cálculos, utilizou-se o método de simulação de Metropolis-Hastings. O software estatístico utilizado neste trabalho foi o R.The meta-analysis role of using Statistics to summarize published studies that have the same goal becomes more essential day by day, due to the improvement of Science and the desire of using the least possible number of human beings in clinical trials, which in many cases is unnecessary. By match the available information it makes the understanding easier and it leads to more robust conclusions. For instance, the increase in the number of clinical researches also makes the need for meta-analysis go higher, arising the need for developing sophisticated techniques. Then our goal in this work is to propose a Bayesian methodology to conduct meta-analysis. The proposed procedure is a blend of posterior distributions from interest parameters of each work we are considering when doing meta-analysis. As a consequence, we have a probability distribution as a meta-analytic measure, rather than just a statistical summary. The methodology we are presenting can be used with any prior probability distribution and any likelihood function. The calculation of the meta-analytic measure has its uses from small to more complex problems. In this work we present some examples that consider various probability distributions and also survival data. There is a sufficient statistic available for the parameter of interest, the posterior probability distribution depends on the data only through this statistic and thus, in many cases, we can reduce our data without loss of information. Some calculations were performed through Metropolis-Hastings simulation algorithm. The statistical software used in this work was the R.
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Kröger, Stefan. "Bioinformatic analyses for T helper cell subtypes discrimination and gene regulatory network reconstruction." Doctoral thesis, Humboldt-Universität zu Berlin, 2017. http://dx.doi.org/10.18452/18122.
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Die Etablierung von Hochdurchsatz-Technologien zur Durchführung von Genexpressionsmessungen führte in den letzten 20 Jahren zu einer stetig wachsende Menge an verfügbaren Daten. Sie ermöglichen durch Kombination einzelner Experimente neue Vergleichsstudien zu kombinieren oder Experimente aus verschiedenen Studien zu großen Datensätzen zu vereinen. Dieses Vorgehen wird als Meta-Analyse bezeichnet und in dieser Arbeit verwendet, um einen großen Genexpressionsdatensatz aus öffentlich zugänglichen T-Zell Experimenten zu erstellen. T-Zellen sind Immunzellen, die eine Vielzahl von unterschiedlichen Funktionen des Immunsystems inititiieren und steuern. Sie können in verschiedene Subtypen mit unterschiedlichen Funktionen differenzieren.
Der mittels Meta-Analyse erstellte Datensatz beinhaltet nur Experimente zu einem T-Zell-Subtyp, den regulatorischen T-Zellen (Treg) bzw. der beiden Untergruppen, natürliche Treg (nTreg) und induzierte Treg (iTreg) Zellen. Eine bisher unbeantwortete Frage lautet, welche subtyp-spezifischen gen-regulatorische Mechanismen die T-Zell Differenzierung steuern. Dazu werden in dieser Arbeit zwei spezifische Herausforderungen der Treg Forschung behandelt: (i) die Identifikation von Zelloberflächenmarkern zur Unterscheidung und Charakterisierung der Subtypen, sowie (ii) die Rekonstruktion von Treg-Zell-spezifischen gen-regulatorischen Netzwerken (GRN), die die Differenzierungsmechanismen beschreiben. Die implementierte Meta-Analyse kombiniert mehr als 150 Microarray-Experimente aus über 30 Studien in einem Datensatz. Dieser wird benutzt, um mittels Machine Learning Zell-spezifische Oberflächenmarker an Hand ihres Expressionsprofils zu identifizieren. Mit der in dieser Arbeit entwickelten Methode wurden 41 Genen extrahiert, von denen sechs Oberflächenmarker sind. Zusätzliche Validierungsexperimente zeigten, dass diese sechs Gene die Experimenten beider T-Zell Subtypen sicher unterscheiden können. Zur Rekonstruktion von GRNs vergleichen wir unter Verwendung des erstellten Datensatzes 11 verschiedene Algorithmen und evaluieren die Ergebnisse mit Informationen aus Interaktionsdatenbanken. Die Evaluierung zeigt, dass die derzeit verfügbaren Methoden nicht in der Lage sind den Wissensstand Treg-spezifischer, regulatorsicher Mechanismen zu erweitern. Abschließend präsentieren wir eine Datenintegrationstrategie zur Rekonstruktion von GRN am Beispiel von Th2 Zellen. Aus Hochdurchsatzexperimenten wird ein Th2-spezifisches GRN bestehend aus 100 Genen rekonstruiert. Während 89 dieser Gene im Kontext der Th2-Zelldifferenzierung bekannt sind, wurden 11 neue Kandidatengene ohne bisherige Assoziation zur Th2-Differenzierung ermittelt. Die Ergebnisse zeigen, dass Datenintegration prinzipiell die GRN Rekonstruktion ermöglicht. Mit der Verfügbarkeit von mehr Daten mit besserer Qualität ist zu erwarten, dass Methoden zur Rekonstruktion maßgeblich zum besseren Verstehen der zellulären Differenzierung im Immunsystem und darüber hinaus beitragen können und so letztlich die Ursachenforschung von Dysfunktionen und Krankheiten des Immunsystems ermöglichen werden.Within the last two decades high-throughput gene expression screening technologies have led to a rapid accumulation of experimental data. The amounts of information available have enabled researchers to contrast and combine multiple experiments by synthesis, one of such approaches is called meta-analysis. In this thesis, we build a large gene expression data set based on publicly available studies for further research on T cell subtype discrimination and the reconstruction of T cell specific gene regulatory events. T cells are immune cells which have the ability to differentiate into subtypes with distinct functions, initiating and contributing to a variety of immune processes. To date, an unsolved problem in understanding the immune system is how T cells obtain a specific subtype differentiation program, which relates to subtype-specific gene regulatory mechanisms. We present an assembled expression data set which describes a specific T cell subset, regulatory T (Treg) cells, which can be further categorized into natural Treg (nTreg) and induced Treg (iTreg) cells. In our analysis we have addressed specific challenges in regulatory T cell research: (i) discriminating between different Treg cell subtypes for characterization and functional analysis, and (ii) reconstructing T cell subtype specific gene regulatory mechanisms which determine the differences in subtype-specific roles for the immune system. Our meta-analysis strategy combines more than one hundred microarray experiments. This data set is applied to a machine learning based strategy of extracting surface protein markers to enable Treg cell subtype discrimination. We identified a set of 41 genes which distinguish between nTregs and iTregs based on gene expression profile only. Evaluation of six of these genes confirmed their discriminative power which indicates that our approach is suitable to extract candidates for robust discrimination between experiment classes. Next, we identify gene regulatory interactions using existing reconstruction algorithms aiming to extend the number of known gene-gene interactions for Treg cells. We applied eleven GRN reconstruction tools based on expression data only and compared their performance. Taken together, our results suggest that the available methods are not yet sufficient to extend the current knowledge by inferring so far unreported Treg specific interactions. Finally, we present an approach of integrating multiple data sets based on different high-throughput technologies to reconstruct a subtype-specific GRN. We constructed a Th2 cell specific gene regulatory network of 100 genes. While 89 of these are known to be related to Th2 cell differentiation, we were able to attribute 11 new candidate genes with a function in Th2 cell differentiation. We show that our approach to data integration does, in principle, allow for the reconstruction of a complex network. Future availability of more and more consistent data may enable the use of the concept of GRN reconstruction to improve understanding causes and mechanisms of cellular differentiation in the immune system and beyond and, ultimately, their dysfunctions and diseases.
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Jeon, Seonghye. "Bayesian data mining techniques in public health and biomedical applications." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43712.
Full textAbstract:
The emerging research issues in evidence-based healthcare decision-making and explosion of comparative effectiveness research (CER) are evident proof of the effort to thoroughly incorporate the rich data currently available within the system. The flexibility of Bayesian data mining techniques lends its strength to handle the challenging issues in the biomedical and health care domains. My research focuses primarily on Bayesian data mining techniques for non-traditional data in this domain, which includes,
1. Missing data: Matched-pair studies with fixed marginal totals with application to meta-analysis of dental sealants effectiveness.
2. Data with unusual distribution: Modeling spatial repeated measures with excess zeros and no covariates to estimate U.S. county level natural fluoride concentration.
3. Highly irregular data: Assess overall image regularity in complex wavelet domain to classify mammography image.
The goal of my research is to strengthen the link from data to decisions. By using Bayesian data mining techniques including signal and image processing (wavelet analysis), hierarchical Bayesian modeling, clinical trials meta-analyses and spatial statistics, this thesis resolves challenging issues of how to incorporate data to improve the systems of health care and bio fields and ultimately benefit public health.
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Santos, João Paulo Aquino. "Estimação das perdas produtivas em frangos de corte devido ao estresse por calor." Universidade Federal de Santa Maria, 2014. http://repositorio.ufsm.br/handle/1/10854.
Full textAbstract:
Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorThe environmental control of sheds for the broiler chickens production can bring better performance results with the reduction of production losses due to heat, and the variations in climatic events may significantly alter the viability of the production system. The objective of this study was to estimate the production loss due to heat in the broiler production system. This research was carried out through a meta- analysis in which 52 related research were used to heat stress in broiler chickens aged 1-42 days old. The data were processed according to the method of meta- analysis and explored by data mining technique for obtaining decision models to assist in the determination and quantification of production losses in broilers. The results demonstrate that the climatic variables the wet bulb temperature and dry bulb temperature in Celsius degrees and the Temperature- Humidity Index (THI ) is possible to estimate the performance loss of broilers influencing low weight gains and worst feed conversions ratio, with values of 32° C dry bulb temperature, relative humidity above 40 % , wet bulb temperature above 25.51 or 25.77º C and 23.29º C of THI as threshold conditions to potential production losses at 30.99% to feed conversion, 36.54% to weight gain and 52.04% to daily weight gain.
O controle da ambiência de galpões para a produção de frangos de corte pode trazer melhores resultados de desempenho devido à redução das perdas produtivas decorrentes do calor, sendo que as variações nos eventos climáticos podem alterar significativamente a viabilidade do sistema produtivo. O objetivo deste trabalho foi estimar as perdas produtivas relacionadas ao calor no sistema de produção de frangos de corte. Este trabalho foi realizado através de uma meta-analise onde foram utilizados 52 trabalhos relacionados com estresse por calor em frangos de corte com idade de 1 a 42 dias. Os dados foram processados segundo o método da meta-análise e explorados pela técnica de Mineração de Dados para a obtenção de modelos decisórios que auxiliem na determinação e quantificação das perdas produtivas em frangos de corte. Os resultados demonstram que por intermédio das variáveis climáticas temperatura de bulbo úmido, a temperatura do bulbo seco em graus Celsius e o índice de temperatura e umidade (ITU) é possível estimar a perda de desempenho dos frangos de corte influenciando os ganhos de peso baixos e conversões alimentares piores, sendo valores de 32º C da temperatura de bulbo seco, umidade relativa do ar acima de 40%, temperatura de bulbo úmido acima de 25,51 ou 25,77º C e ITU de 23,29º C como condições limite para a ocorrência de perdas produtivas potenciais de até 30,99% para a conversão alimentar, 36,54% no ganho de peso e 52,04% no ganho de peso médio diário.
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Bazile, Jeanne. "Intégration de données publiques et analyses protéomiques pour révéler les mécanismes et biomarqueurs du dépôt de lipides dans la carcasse ou le muscle bovin." Thesis, Université Clermont Auvergne (2017-2020), 2019. http://www.theses.fr/2019CLFAC074.
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L’équilibre entre les masses des tissus musculaire (TM) et adipeux (TA) conditionne le poids de carcasse et son rendement (rapport TM et TA), mais aussi les qualités sensorielle et nutritionnelle des viandes. Comprendre comment contrôler le rapport des masses de muscle relativement à celle des tissus adipeux reste un enjeu majeur pour les filières de production bovine. Les méthodes omiques ont abondamment été utilisées pour comprendre les mécanismes explicatifs de la variabilité du croît ou de la masse des tissus adipeux et musculaire chez le bovin. Cependant, à partir de cette masse de données, il n’est pas toujours aisé d’extraire ou de générer une information biologique synthétique. L’objectif de ma thèse était donc d’agréger et de ré-analyser des données publiques pour proposer des gènes ou protéines marqueurs de l’adiposité corporelle ou musculaire, compléter les connaissances disponibles ou identifier des manques de données. Pour ce faire, des techniques in silico et expérimentale ont été combinées. La majorité des données disponibles dans les bases publiques concernaient le muscle et étaient des données transcriptomiques, rarement protéomiques. Les résultats de 5 publications comparant le protéome musculaire de bovins divergents pour la teneur en lipides intramusculaires ont été agrégés pour identifier 50 protéines avec des abondances divergentes, dont 9 trouvées dans au moins 2 publications. Ces données ayant été obtenues chez des races précoces, nous avons analysé le protéome d’une race plus tardive. Le muscle Longissimus thoracis de bovins, Rouges des Prés divergents par les adiposités musculaire et corporelle ont été analysés par les techniques de shotgun et de 2DE. Sur les 47 protéines liées significativement aux dépôts adipeux dans le muscle ou la carcasse, 21 étaient communes avec les résultats publiés, et 26 n’avaient jamais été identifiées. En particulier, l’abondance d’APOBEC2 était fortement corrélée à l’adiposité de la carcasse et du muscle.Parmi les données issues de puces à ADN accessibles dans les bases de données publiques, 84 et 12 jeux de données relatifs, respectivement à la croissance musculaire et adipeuse, ont été sélectionnés. En raison de manques dans les métadonnées, seulement 33 (32 « TM », 1 « TA ») d’entre eux ont été rendus comparables par la mise à jour des noms de gène sur le génome bovin actuel (UCD1.2 ; collaboration avec Sigenae). Les données des 32 jeux de données « muscle » ont été catégorisées selon l’âge, la race, le sexe ou l’alimentation. Par catégorie, les données ont été regroupées et analysées par combinaison de valeurs p selon la méthode inverse normale (collaboration avec l’UMR Gabi). Pour la catégorie âge, facteur de variation majeur de la teneur en lipides intramusculaires, nous avons identifié 238 gènes (sur les 715 communs à 10 jeux de données) différentiellement exprimés dans le longissimus dorsi de bovins de 5 races. Parmi ces 238 gènes, 97 étaient différentiels dans au moins 2 des jeux de données analysés individuellement et la méta-analyse. Ils confirmaient par exemple la dynamique de régulation des métabolismes glycolytiques et oxydatif en fonction de l’âge des bovins. 17 gènes ont été identifiés comme différentiel selon l’âge exclusivement dans la méta-analyse. Parmi les gènes identifiés certains sont liés au métabolisme des lipides (APOE, LDLR, MXRA8) et d’autres pourraient induire (YBX1) ou réprimer (MAPK14, YWAH, ERBB2), la différenciation de cellules progénitrices musculaires vers le lignage adipeux. L’intégration de données publiques, notamment par la méta-analyse, a donc augmenté les connaissances sur les mécanismes biologiques et biomarqueurs contribuant au rapport TA/TM. Les relations entre les abondances des molécules identifiées et des critères d’adiposité restent à quantifier dans une perspective de validation des biomarqueursProducing meat animals with adequate muscular and adipose masses (i.e. lean-to-fat ratio) is an economic challenge for the beef industry. The lean-to-fat ratio influence weight and yield of carcasses as well as the sensorial and nutritional quality of the meat. Omics methods have been widely used to understand mechanisms underlying the variability of the adipose and muscle tissue growth in the bovine. However, it is not always easy to extract or generate a synthetic biological information from this volume of data. The objective of my thesis was to aggregate and analyse public data to propose genes or proteins related to the lean-to-fat, and to identify data to be completed by experiment. To achive this goal, experimental and in silico methods were combined.Majority of available data in public databases were muscle transcriptomic data, and very rarely proteomic data. Data from 5 publications comparing muscle proteome of bovine breeds divergent in their intramuscular lipid content were aggregated and allowed the identification of 50 differently abundant proteins. Of these, 9 were concordant in at least 2 publications. As those data were obtained only in late-maturing breeds, we analysed proteome of “Rouges des Prés” cows which deposit fat in a later stage of development. Longissimus thoracis muscle of bovine “Rouges des prés”, that diverges in their muscular and corporal adiposity were analysed by shotgun and 2DE techniques. Of the 47 proteins significatively associated to adipose depots in muscle or carcass, 21 were common to published data and 26 had never been identified before. Particularly, APOBEC2 abundance was strongly correlated with both carcass and muscle adiposity.Among the microarray data available in the public databases, 84 and 12 datasets relative to muscular and adipose growth were selected, respectively. Because of missing metadata, only 33 (32 “MT” and 1 “AT”) were used and their identifiers updated on the current bovine genome (UCD1.2; collaboration with Sigenae). Data of 32 “muscle” datasets were categorized according to the age, breed, sex or nutrition. Data were regrouped by categories and analysed by p-value combination according to the inverse normal method (collaboration with Gabi UMR). For the age category, a major factor influencing intramuscular lipid content, we identified 238 genes differentially expressed between two ages in longissimus dorsi of bovine of 5 different breeds. Among these 238 genes, 97 were identified in at least 2 datasets analysed individually and in the meta-analysis. The meta-analysis confirmed the dynamic regulation of glycolytic and oxidative metabolisms depending on bovine age. 17 genes were exclusively identified in the meta-analysis as differentially expressed between two ages. Among the identified genes, some are linked to lipid metabolism (APOE, LDLR, MXRA8) and other may induce (YBX1) or repress (MAPK14, YWAH, ERBB2) the differentiation of muscle progenitor cells towards the adipose lineage.Integration of public data, in particular by the meta-analysis, provided a global view of biological mechanisms and biomarkers (genes or proteins) of the lean-to-fat ratio that were the most frequently identified in several breeds. The relationships between the abundances of the identified molecules and adiposity criteria remain to be quantified in a perspective of biomarker validation (prior to animal slaughter/ without the need to slaughter the animal).Integration of public data, in particular by the meta-analysis, allowing to aquire a global view of biological mechanisms and biomarkers (genes or proteins) of the AT to MT ratio. This approach will allow to check and evaluate carcass and muscle AT percentage from gene or protein abundance prior to animal slaughter/ without the need to slaughter the animal
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Branco, Tatiane. "Concentração e emissão de amônia em aviários de frango de corte." Universidade Federal de Santa Maria, 2017. http://repositorio.ufsm.br/handle/1/11351.
Full textAbstract:
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPESThe aerial environment in broiler houses requires differentiated management depending on the time of year to maintain an ammonia concentration below 10 ppm, optimal condition for broilers, and adequate performance and well-being. The ammonia is volatilized from the microbial decomposition in the poultry litter and dependent on several factors, among them, internal and external environmental conditions, litter characteristics and facility typology. The systematization and analysis of data can help in to understanding studies that contain a variability of interferences, like an aerial ambience; and a data mining is a technique that has the function of analyzing the generated database. Three studies were carried out to evaluate the production of ammonia in broiler houses in conditions of heat and mild climate, by means of meta-analysis and environmental measurement. The first study resulted in an ammonia concentration database using the meta-analysis technique. Data analysis was with data mining technique, using two ammonia concentration classes: less than 20 ppm and equal or above this limit. Negative pressure facilities presented high ammonia concentration and morning time presented an ammonia concentration equal or above 20 ppm. Conventional facilities, using wood shavings and stoking density whit more than 15 birds m-2 had an ammonia concentration classification above the ideal limit (≥ 20 ppm). The second study provided a meta-analysis of the ammonia emission that allowed, through the data mining technique, to obtain two classification approaches: a) high ammonia emission levels (≥ 42.2 mg Kg-1 of poultry litter) and b) low ammonia emission levels (<42.2 mg Kg-1 poultry litter). Only Dark House was qualified for “High” ammonia emission due the winter season. The wood shavings poultry litter presented low emission when in conventional houses, in contrast to rice husk (high ammonia emission). Poultry litter whit above 8.3 and stocking density greater than 12 birds m-2 obtained “High” ammonia emission classification. In the third study the ammonia concentration, air velocity, internal and external temperature were collected in six broiler houses of different typologies and climatic conditions of heat, being analyzed by geostatistics. The concentration of ammonia tends to be higher in the central and final part of the broiler houses, places where the internal temperature was higher. Better ventilation maneuvers could solve the problems with high temperature and ammonia concentration throughout the broiler houses. The results observed in the concentration and ammonia emission meta-analysis point to conditions of facilities and characteristics of the poultry litter. Data mining allowed the evaluation of ammonia production in different typologies of aviaries in a systematic way through two databases constructed by the meta-analysis technique. The rules of the figure models allowed extracting coherent and useful knowledge in meta-analysis databases. The use of maps of variability is another suitable means for the evaluation of variables such as ammonia concentration and internal temperature. However, several factors influence and, if handled correctly, can minimize the emission and concentration of ammonia inside the broiler house. Combining the thermal and aerial ambience with the ventilation system is an option to improve the welfare indexes in broilers.
O ambiente aéreo em aviários de frango de corte exige manejos diferenciados conforme a época do ano para manter a concentração de amônia abaixo de 10 ppm, condição ótima para frangos de corte apresentarem desempenho e bem-estar adequados. A amônia é volatilizada a partir da decomposição microbiana na cama de frango aviária e dependente de vários fatores, entre eles, condições ambientais internas e externas, características da cama e tipologia de aviário. A sistematização e análise de dados podem auxiliar na compreensão de estudos que contenham uma variabilidade de interferentes, como a ambiência aérea; e a mineração de dados é uma técnica que tem função de analisar o banco de dados gerado. Foram realizados três estudos para avaliar a produção de amônia em galpões de frango de corte durante condições de calor e clima ameno, por intermédio de metanálise e mensuração do ambiente. O primeiro estudo resultou em um banco de dados de concentração de amônia por meio da técnica de metanálise. A análise dos dados foi realizada por meio da técnica de mineração de dados para as classes de concentração de amônia menor que 20 ppm e igual ou acima deste limite. Aviários de pressão negativa apresentaram altas concentrações de amônia e o horário de coleta no turno da manhã apresentou condição de concentração de amônia igual ou acima de 20 ppm. Aviários de tipologia convencional, utilizando maravalha e com densidade de criação maiores de 15 aves m-2 obtiveram classificação de concentração de amônia acima do limite ideal (≥ 20 ppm). O segundo estudo propiciou uma metanálise da emissão de amônia que permitiu, por meio da técnica de mineração de dados, obter duas abordagens de classificação: a) altos níveis de emissão de amônia (≥ 42,2 mg Kg-1 de cama de frango) e b) baixos níveis de emissão de amônia (< 42,2 mg Kg-1 de cama de frango). Aviário de tipologia Dark House foi o único que se classificou para a emissão de amônia em “Elevada” em função da estação do ano ser inverno. A cama de frango de maravalha de madeira apresentou menor emissão em aviários convencionais, ao contrário da casca de arroz (alta emissão de amônia). Cama de aviário com pH acima de 8,3 e densidade de criação maiores de 12 aves m-² obtiveram classificação como “Elevada” emissão de amônia. No terceiro estudo foi realizado a coleta de concentração de amônia, velocidade do ar, temperatura interna e externa em seis aviários de tipologias diferentes e condições climáticas de calor, sendo analisados por meio da geoestatística. A concentração de amônia tende a ser maior na parte central e final dos aviários, lugares em que foi constatado maior temperatura interna. Melhores manejos de ventilação poderiam solucionar os problemas com temperatura alta e concentração de amônia ao longo dos aviários. Os resultados observados nas metanálises de concentração e emissão de amônia apontam para condições de instalações e características da cama de frango. A mineração de dados permitiu avaliar a produção de amônia em diferentes tipologias de aviários de forma sistemática por meio de dois bancos de dados construídos pela técnica de metanálise. As regras dos modelos permitiram extrair conhecimentos coerentes e úteis para os dois bancos de dados metanalíticos. A utilização de mapas de variabilidade é outro meio adequado para a avaliação de variáveis como a concentração de amônia e a temperatura interna. No entanto, vários fatores influenciam e, se manejados corretamente, podem minimizar a emissão e concentração de amônia no interior da instalação. Aliar a ambiência térmica e aérea em função do sistema de ventilação é uma opção para melhorar os índices de bem-estar em frangos de corte.