Thematische Bibliographien / Statistical association

Auswahl der wissenschaftlichen Literatur zum Thema „Statistical association“

Autor: Grafiati

Veröffentlicht am 15. September 2021

Zuletzt aktualisiert am 14. Februar 2022

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Zeitschriftenartikel zum Thema "Statistical association":

Borgan, Ørnulf, und Marie Lilleborge. „The Norwegian Statistical Association“. EMS Newsletter 2019-6, Nr. 112 (06.06.2019): 39–40. http://dx.doi.org/10.4171/news/112/10.

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de Macedo, Carmen. „Guilt by Statistical Association“. Journal of Philosophy 105, Nr. 6 (2008): 320–32. http://dx.doi.org/10.5840/jphil2008105640.

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Hennekens, Charles H. „Statistical Association and Causation“. JAMA 305, Nr. 11 (16.03.2011): 1134. http://dx.doi.org/10.1001/jama.2011.322.

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Qu, Hui-Qi, Matthew Tien und Constantin Polychronakos. „Statistical significance in genetic association studies“. Clinical & Investigative Medicine 33, Nr. 5 (01.10.2010): 266. http://dx.doi.org/10.25011/cim.v33i5.14351.

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Clinical & Investigative Medicine (CIM) is receiving an increasing number of reports of candidate-based association studies. The track record of such studies in the past has been poor: numerous genetic associations reported from candidate gene studies have not been replicated in later studies. The rise of the genome-wide association study (GWAS) is changing this situation. A well-designed GWAS may identify a number of candidate loci without bias by screening the whole human genome. Validating and fine-mapping the candidate loci from GWAS are required to clarify the genetic mechanisms. Thus, a candidate-based association study has become a well-directed effort, instead of searching for a needle in a haystack. In the post-GWAS era, exponential growth of candidate-based genetic association studies is expected. A pressing issue accompanying this new trend is the assessment of the validity of an association study. In this editorial, we illustrate the major cause of false positive association from random sampling bias by an empirical example, and emphasize the application of the probability theory in assessing the validity of a genetic association study.

Schröer, Wolffram, und Volker C. Weiss. „Molecular association in statistical thermodynamics“. Journal of Molecular Liquids 205 (Mai 2015): 22–30. http://dx.doi.org/10.1016/j.molliq.2014.08.013.

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Sapra, RameshLal, und Satish Saluja. „Understanding statistical association and correlation“. Current Medicine Research and Practice 11, Nr. 1 (2021): 31. http://dx.doi.org/10.4103/cmrp.cmrp_62_20.

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Gilchrist, Martin. „Springer and the American Statistical Association“. CHANCE 5, Nr. 1-2 (Januar 1992): 4. http://dx.doi.org/10.1080/09332480.1992.11882453.

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Banerjee, P. K. „Fifty Years of Calcutta Statistical Association“. Calcutta Statistical Association Bulletin 45, Nr. 1-2 (März 1995): 1–24. http://dx.doi.org/10.1177/0008068319950101.

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Bruzzese, Dario, und Cristina Davino. „Statistical Pruning of Discovered Association Rules“. Computational Statistics 16, Nr. 3 (September 2001): 387–98. http://dx.doi.org/10.1007/s001800100074.

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Weiß, Christian H. „Statistical mining of interesting association rules“. Statistics and Computing 18, Nr. 2 (21.12.2007): 185–94. http://dx.doi.org/10.1007/s11222-007-9047-6.

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Dissertationen zum Thema "Statistical association":

ZHANG, GE. „STATISTICAL METHODS IN GENETIC ASSOCIATION“. University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1196099744.

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Perry, Martin Andrew. „Statistical linkage analysis and association studies“. Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp01/MQ57208.pdf.

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Kazeem, Gbenga Rahman. „Statistical analysis of genetic-association studies“. Thesis, University of Oxford, 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.426396.

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Mastrodomenico, Robert. „Statistical analysis of genetic association studies“. Thesis, University of Reading, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.515692.

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Alshahrani, Mohammed Nasser D. „Statistical methods for rare variant association“. Thesis, University of Leeds, 2018. http://etheses.whiterose.ac.uk/22436/.

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Deoxyribonucleic acid (DNA) sequencing allows researchers to conduct more complete assessments of low-frequency and rare genetic variants. In anticipation of the availability of next-generation sequencing data, there is increasing interest in investigating associations between complex traits and rare variants (RVs). In contrast to association studies of common variants (CVs), due to the low frequencies of RVs, common wisdom suggests that existing statistical tests for CVs might not work, motivating the recent development of several new tests that analyze RVs, most of which are based on the idea of pooling/collapsing RVs. Genome-wide association studies (GWAS) based on common SNPs gained more attention in the last few years and have been regularly used to examine complex genetic compositions of diseases and quantitative traits. GWASs have not discovered everything associated with diseases and genetic variations. However, recent empirical evidence has demonstrated that low-frequency and rare variants are, in fact, connected to complex diseases. This thesis will focus on the study of rare variant association. Aggregation tests, where multiple rare variants are analyzed jointly, have incorporated weighting schemes on variants. However, their power is very much dependent on the weighting scheme. I will address three topics in this thesis: the definition of rare variants and their call file (VCF) and a description of the methods that have been used in rare variant analysis. Finally, I will illustrate challenges involved in the analysis of rare variants and propose different weighting schemes for them. Therefore, since the efficiency of rare variant studies might be considerably improved by the application of an appropriate weighting scheme, choosing the proper weighting scheme is the topic of the thesis. In the following chapters, I will propose different weighting schemes, where weights are applied at the level of the variant, the individual or the cell (i.e. the individual genotype call), as well as a weighting scheme that can incorporate quality measures for variants (i.e., a quality score for variant calls) and cells (i.e., genotype quality).

Dai, Xiaotian. „Novel Statistical Models for Quantitative Shape-Gene Association Selection“. DigitalCommons@USU, 2017. https://digitalcommons.usu.edu/etd/6856.

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Other research reported that genetic mechanism plays a major role in the development process of biological shapes. The primary goal of this dissertation is to develop novel statistical models to investigate the quantitative relationships between biological shapes and genetic variants. However, these problems can be extremely challenging to traditional statistical models for a number of reasons: 1) the biological phenotypes cannot be effectively represented by single-valued traits, while traditional regression only handles one dependent variable; 2) in real-life genetic data, the number of candidate genes to be investigated is extremely large, and the signal-to-noise ratio of candidate genes is expected to be very high. In order to address these challenges, we propose three statistical models to handle multivariate, functional, and multilevel functional phenotypes, with applications to biological shape data using different shape descriptors. To the best of our knowledge, there is no statistical model developed for multilevel functional phenotypes. Even though multivariate regressions have been well-explored and these approaches can be applied to genetic studies, we show that the model proposed in this dissertation can outperform other alternatives regarding variable selection and prediction through simulation examples and real data examples. Although motivated ultimately by genetic research, the proposed models can be used as general-purpose machine learning algorithms with far-reaching applications.

Huang, Bevan Emma Lin Danyu. „Statistical aspects of haplotype-based association studies“. Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,1237.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2007.
Title from electronic title page (viewed Mar. 26, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biostatistics, School of Public Health." Discipline: Biostatistics; Department/School: Public Health.

Teo, Yik Ying. „Statistical challenges arising in genomewide association studies“. Thesis, University of Oxford, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.436942.

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Koh, Hyunwook. „Adaptive Statistical Methods for Microbiome Association Studies“. Thesis, New York University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10750033.

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The human microbiome studies have been accelerated by the advances in next-generation sequencing technologies. There has also been increasing interest in discovering microbial taxa that are associated with diverse host phenotypes, environmental factors or clinical interventions. Here, I first describe unique features of microbiome data and the resulting demand for adaptive association analysis which robustly suits different association patterns, while providing valid statistical inferences. Then, I introduce two adaptive microbiome association tests as follows.

My first method, namely, optimal microbiome-based association test (OMiAT), relates microbial composition with continuous (e.g., body mass index) or binary (e.g., disease status) traits. OMiAT is a data-driven adaptive testing method which approximates to the most powerful performance among different candidate tests from the sum of powered score tests (SPU) and microbiome regression-based kernel association test (MiRKAT). I illustrate that OMiAT robustly discovers underlying association signals arising from highly imbalanced microbial abundances and phylogenetic tree structure, while correctly controlling type I error rates. I also propose a way to apply it to fine association mapping of diverse higher-level taxa at different taxonomic levels within a newly introduced microbial taxa discovery framework, microbiome comprehensive association mapping (MiCAM).

My second method, namely, optimal microbiome-based survival analysis (OMiSA), relates microbial composition with survival (i.e., time to event) traits. OMiSA approximates to the most powerful association test within two test domains, 1) microbiome-based survival analysis using linear and non-linear bases of OTUs (MiSALN) and 2) microbiome-based kernel association test for survival traits (MiRKAT-S). I illustrate that OMiSA powerfully discovers underlying associated lineages whether they are rare or abundant and phylogenetically related or not, while correctly controlling type I error rates.

OMiAT and OMiSA are attractive in practice due to the high complexity of microbiome data and the unknown true nature of the state. MiCAM also provides a hierarchical microbiome association map through a breadth of taxonomic levels, which can be used as a guideline for further investigation on the roles of discovered taxa in human health or disease.

Liley, Albert James. „Statistical co-analysis of high-dimensional association studies“. Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270628.

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Modern medical practice and science involve complex phenotypic definitions. Understanding patterns of association across this range of phenotypes requires co-analysis of high-dimensional association studies in order to characterise shared and distinct elements. In this thesis I address several problems in this area, with a general linking aim of making more efficient use of available data. The main application of these methods is in the analysis of genome-wide association studies (GWAS) and similar studies. Firstly, I developed methodology for a Bayesian conditional false discovery rate (cFDR) for levering GWAS results using summary statistics from a related disease. I extended an existing method to enable a shared control design, increasing power and applicability, and developed an approximate bound on false-discovery rate (FDR) for the procedure. Using the new method I identified several new variant-disease associations. I then developed a second application of shared control design in the context of study replication, enabling improvement in power at the cost of changing the spectrum of sensitivity to systematic errors in study cohorts. This has application in studies on rare diseases or in between-case analyses. I then developed a method for partially characterising heterogeneity within a disease by modelling the bivariate distribution of case-control and within-case effect sizes. Using an adaptation of a likelihood-ratio test, this allows an assessment to be made of whether disease heterogeneity corresponds to differences in disease pathology. I applied this method to a range of simulated and real datasets, enabling insight into the cause of heterogeneity in autoantibody positivity in type 1 diabetes (T1D). Finally, I investigated the relation of subtypes of juvenile idiopathic arthritis (JIA) to adult diseases, using modified genetic risk scores and linear discriminants in a penalised regression framework. The contribution of this thesis is in a range of methodological developments in the analysis of high-dimensional association study comparison. Methods such as these will have wide application in the analysis of GWAS and similar areas, particularly in the development of stratified medicine.

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Bücher zum Thema "Statistical association":

Wong, Raymond Sin-Kwok. Association models. Thousand Oaks: Sage, 2010.

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Wong, Raymond Sin-Kwok. Association models. Thousand Oaks: Sage, 2010.

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Wong, Raymond Sin-Kwok. Association models. Thousand Oaks: Sage, 2010.

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Gibbons, Jean Dickinson. Nonparametric measures of association. Newbury Park: Sage Publications, 1993.

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Neale, Benjamin M. Statistical genetics: Gene mapping through linkage and association. New York: Taylor & Francis Group, 2008.

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Foulkes, Andrea S. Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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Foulkes, Andrea S. Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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Foulkes, Andrea S. Applied statistical genetics with R: For population-based association studies. New York: Springer Verlag, 2009.

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Association, Bangladesh Statistical. Directory of members 2010. Dhaka: Bangladesh Statistical Association, 2010.

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Association, Bangladesh Statistical. Directory of members, 2012. Dhaka: Bangladesh Statistical Association, 2012.

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Buchteile zum Thema "Statistical association":

Sy, Bon K., und Arjun K. Gupta. „Statistical Association Patterns“. In The Kluwer International Series in Engineering and Computer Science, 99–112. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4419-9001-3_8.

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Clayton, D. „Population Association“. In Handbook of Statistical Genetics, 1216–37. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch36.

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Berry, Kenneth J., Janis E. Johnston und Paul W. Mielke. „Permutation Statistical Methods“. In The Measurement of Association, 19–71. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-98926-6_2.

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Hahs-Vaughn, Debbie L., und Richard G. Lomax. „Bivariate Measures of Association“. In Statistical Concepts, 369–416. New York, NY : Routledge, 2019.: Routledge, 2020. http://dx.doi.org/10.4324/9780429261268-10.

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Dickhaus, Thorsten. „Genetic Association Studies“. In Simultaneous Statistical Inference, 129–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-45182-9_9.

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Sabo, Roy, und Edward Boone. „Association and Regression“. In Statistical Research Methods, 181–209. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8708-1_10.

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Lysenko, Artem, Keith A. Boroevich und Tatsuhiko Tsunoda. „Genotyping and Statistical Analysis“. In Genome-Wide Association Studies, 1–20. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8177-5_1.

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Morris, A. P., und L. R. Cardon. „Whole Genome Association“. In Handbook of Statistical Genetics, 1238–63. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch37.

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Dudbridge, F. „Family-Based Association“. In Handbook of Statistical Genetics, 1264–85. Chichester, UK: John Wiley & Sons, Ltd, 2008. http://dx.doi.org/10.1002/9780470061619.ch38.

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Gupta, Arjun K., Wei-Bin Zeng und Yanhong Wu. „Association and Dependence“. In Probability and Statistical Models, 141–57. Boston, MA: Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-4987-6_7.

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Konferenzberichte zum Thema "Statistical association":

Deignan, Paul B. „Estimation of entropic measures of association“. In 2011 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2011. http://dx.doi.org/10.1109/ssp.2011.5967812.

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Jian, Hu, und Yang-Li Xiang. „Association Rules Mining Based on Statistical Correlation“. In 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2008. http://dx.doi.org/10.1109/wicom.2008.2571.

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Aumann, Yonatan, und Yehuda Lindell. „A statistical theory for quantitative association rules“. In the fifth ACM SIGKDD international conference. New York, New York, USA: ACM Press, 1999. http://dx.doi.org/10.1145/312129.312243.

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Asmui, Mas’udah, Suhanom Mohd Zaki, Sharifah Norhuda Syed Wahid, Noorsuraya Mohd Mokhtar und Siti Suhaila Harith. „Association between litterers’ profile and littering behavior: A chi-square approach“. In THE 3RD ISM INTERNATIONAL STATISTICAL CONFERENCE 2016 (ISM-III): Bringing Professionalism and Prestige in Statistics. Author(s), 2017. http://dx.doi.org/10.1063/1.4982841.

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Singer, Paul Frank. „Track-to-track association using intrinsic statistical properties“. In Optical Engineering + Applications, herausgegeben von Oliver E. Drummond und Richard D. Teichgraeber. SPIE, 2007. http://dx.doi.org/10.1117/12.735699.

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Brambilla, Mattia, Gloria Soatti und Monica Nicoli. „Precise Vehicle Positioning by Cooperative Feature Association and Tracking in Vehicular Networks“. In 2018 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2018. http://dx.doi.org/10.1109/ssp.2018.8450794.

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Reynar, Jeffrey C. „Statistical models for topic segmentation“. In the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA: Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034735.

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Collins, Michael, Lance Ramshaw, Jan Hajič und Christoph Tillmann. „A statistical parser for Czech“. In the 37th annual meeting of the Association for Computational Linguistics. Morristown, NJ, USA: Association for Computational Linguistics, 1999. http://dx.doi.org/10.3115/1034678.1034754.

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Lan Phuong Phan, Hiep Xuan Huynh, Hung Huu Huynh und Ky Minh Nguyen. „Association-based recommender system using statistical implicative cohesion measure“. In 2016 Eighth International Conference on Knowledge and Systems Engineering (KSE). IEEE, 2016. http://dx.doi.org/10.1109/kse.2016.7758044.

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Chen, Zhibo, Carlos Ordonez und Kai Zhao. „Comparing Reliability of Association Rules and OLAP Statistical Tests“. In 2008 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2008. http://dx.doi.org/10.1109/icdmw.2008.76.

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Berichte der Organisationen zum Thema "Statistical association":

Cooley, Philip, Robert Clark und Ralph Folsom. Assessing Gene-Environment Interactions in Genome-Wide Association Studies: Statistical Approaches. RTI Press, Mai 2014. http://dx.doi.org/10.3768/rtipress.2014.rr.0022.1405.

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Brenner, David J. Travel for the 2004 American Statistical Association Biannual Radiation Meeting: "Radiation in Realistic Environments: Interactions Between Radiation and Other Factors. Office of Scientific and Technical Information (OSTI), Juli 2009. http://dx.doi.org/10.2172/960220.

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Sánchez-Páez, David A. Effects of income inequality on COVID-19 infections and deaths during the first wave of the pandemic: Evidence from European countries. Verlag der Österreichischen Akademie der Wissenschaften, August 2021. http://dx.doi.org/10.1553/populationyearbook2022.res1.1.

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Evidence from research on infectious diseases suggests that income inequality is related to higher rates of infection and death in disadvantaged population groups. Our objective is to examine whether there was an association between income inequality and the numbers of cases and deaths during the first wave of the COVID- 19 pandemic in European countries. We determined the duration of the first wave by first smoothing the number of daily cases, and then using a LOESS regression to fit the smoothed trend. Next, we estimated quasi-Poisson regressions. Results from the bivariate models suggest there was a moderate positive association between the Gini index values and the cumulated number of infections and deaths during the first wave, although the statistical significance of this association disappeared when controls were included. Results from multivariate models suggest that higher numbers of infections and deaths from COVID-19 were associated with countries having more essential workers, larger elderly populations and lower health care capacities.

Jung, Carina, Matthew Carr, Eric Fleischman und Chandler Roesch. Response of the green June beetle and its gut microbiome to RDX and phenanthrene. Engineer Research and Development Center (U.S.), November 2020. http://dx.doi.org/10.21079/11681/38799.

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Green June beetles are a cosmopolitan pest in the United States. Adults are voracious consumers of tree and vine fruit, while their larvae can dam-age and inadvertently consume root systems, particularly those of grasses, as they move through the soil and forage for detritus. Larvae ingest and process large volumes of soil while in the process of feeding. Due to their intimate contact with the soil it was hypothesized that soil contaminants that are known animal toxins would perturb the larval and affect their overall health and survival. Studies of this kind are important contribu-tions to the development of new model organisms and our understanding of interactions between the environment, contaminants, gut microbiome, and animal development, health, and survival. It is important to continue to develop relevant model organisms for monitoring toxicity as regulations for working with vertebrates becomes more prohibitive. In this study green June beetle larvae were exposed to RDX and phenanthrene through-out their entire soil-bound development, starting within the first few days of hatching through to their emergence as adults. The overall findings included that even at high concentrations, RDX and phenanthrene (25 ppm) exerted no significant effect on body weight or survival. Also, there was lit-tle apparent effect of RDX and phenanthrene on the bacterial microbiome, and no statistical association with measurable health effects. Nevertheless, the green June beetle is an interesting model for soil toxicity experiments in the future as is it easy to collect, house, and handle.

Hutchinson, M. L., J. E. L. Corry und R. H. Madden. A review of the impact of food processing on antimicrobial-resistant bacteria in secondary processed meats and meat products. Food Standards Agency, Oktober 2020. http://dx.doi.org/10.46756/sci.fsa.bxn990.

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For meat and meat products, secondary processes are those that relate to the downstream of the primary chilling of carcasses. Secondary processes include maturation chilling, deboning, portioning, mincing and other operations such as thermal processing (cooking) that create fresh meat, meat preparations and ready-to-eat meat products. This review systematically identified and summarised information relating to antimicrobial resistance (AMR) during the manufacture of secondary processed meatand meat products (SPMMP). Systematic searching of eight literature databases was undertaken and the resultantpapers were appraised for relevance to AMR and SPMMP. Consideration was made that the appraisal scores, undertaken by different reviewers, were consistent. Appraisal reduced the 11,000 initially identified documents to 74, which indicated that literature relating to AMR and SPMMP was not plentiful. A wide range of laboratory methods and breakpoint values (i.e. the concentration of antimicrobial used to assess sensitivity, tolerance or resistance) were used for the isolation of AMR bacteria.The identified papers provided evidence that AMR bacteria could be routinely isolated from SPMMP. There was no evidence that either confirmed or refuted that genetic materials capable of increasing AMR in non-AMR bacteria were present unprotected (i.e. outside of a cell or a capsid) in SPMMP. Statistical analyses were not straightforward because different authors used different laboratory methodologies.However, analyses using antibiotic organised into broadly-related groups indicated that Enterobacteriaceaeresistant to third generation cephalosporins might be an area of upcoming concern in SPMMP. The effective treatment of patients infected with Enterobacteriaceaeresistant to cephalosporins are a known clinical issue. No AMR associations with geography were observed and most of the publications identified tended to be from Europe and the far east.AMR Listeria monocytogenes and lactic acid bacteria could be tolerant to cleaning and disinfection in secondary processing environments. The basis of the tolerance could be genetic (e.g. efflux pumps) or environmental (e.g. biofilm growth). Persistent, plant resident, AMR L. monocytogenes were shown by one study to be the source of final product contamination. 4 AMR genes can be present in bacterial cultures used for the manufacture of fermented SPMMP. Furthermore, there was broad evidence that AMR loci could be transferred during meat fermentation, with refrigeration temperatures curtailing transfer rates. Given the potential for AMR transfer, it may be prudent to advise food business operators (FBOs) to use fermentation starter cultures that are AMR-free or not contained within easily mobilisable genetic elements. Thermal processing was seen to be the only secondary processing stage that served as a critical control point for numbers of AMR bacteria. There were significant linkages between some AMR genes in Salmonella. Quaternary ammonium compound (QAC) resistance genes were associated with copper, tetracycline and sulphonamide resistance by virtue of co-location on the same plasmid. No evidence was found that either supported or refuted that there was any association between AMR genes and genes that encoded an altered stress response or enhanced the survival of AMR bacteria exposed to harmful environmental conditions.