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Relevant bibliographies by topics / Meta-data-analysis

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Academic literature on the topic 'Meta-data-analysis'

Author: Grafiati

Published: 4 June 2021

Last updated: 9 February 2022

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Journal articles on the topic "Meta-data-analysis"

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C., Kalpana. "Health Care Data Analysis through Machine Learning Meta Heuristic Algorithm." Journal of Advanced Research in Dynamical and Control Systems 12, no. 7 (July 20, 2020): 196–201. http://dx.doi.org/10.5373/jardcs/v12i7/20202000.

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Kober, Hedy, and Tor D. Wager. "Meta‐analysis of neuroimaging data." Wiley Interdisciplinary Reviews: Cognitive Science 1, no. 2 (February 24, 2010): 293–300. http://dx.doi.org/10.1002/wcs.41.

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White, Ian R., and Julian P. T. Higgins. "Meta-analysis with Missing Data." Stata Journal: Promoting communications on statistics and Stata 9, no. 1 (March 2009): 57–69. http://dx.doi.org/10.1177/1536867x0900900104.

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Messori, Andrea, Sabrina Trippoli, Monica Vaiani, and Francesco Cattel. "Survival Meta-Analysis of Individual Patient Data and Survival Meta-Analysis of Published (Aggregate) Data." Clinical Drug Investigation 20, no. 5 (November 2000): 309–16. http://dx.doi.org/10.2165/00044011-200020050-00002.

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Oh, In-Sue. "Beyond Meta-Analysis: Secondary Uses of Meta-Analytic Data." Annual Review of Organizational Psychology and Organizational Behavior 7, no. 1 (January 21, 2020): 125–53. http://dx.doi.org/10.1146/annurev-orgpsych-012119-045006.

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Secondary uses of meta-analytic data (SUMAD) represent advanced analyses and applications of first-order meta-analytic results for theoretical (e.g., theory testing) and practical (e.g., evidence-based practice) purposes to produce novel knowledge that cannot be directly obtained from the input meta-analytic results. First-order meta-analytic results in the form of bivariate effect sizes have been used as input to such secondary analyses and applications. Given the increasing popularity of SUMAD in human resource management (HRM) and organizational behavior (OB), there is a need for a systematic review on this topic. This article has two primary goals. First, it reviews essential works regarding SUMAD in the fields of HRM/OB and provides taxonomies of SUMAD in theoretical and practical domains. Second, it introduces recent SUMAD and discusses future directions that encourage more innovative and rigorous research endeavors along this line.

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Tikito, Iman, Mohammed El Arass, and Nissrine Souissi. "Meta-Analysis of Data Collect Methods." Journal of Computer Science 15, no. 8 (August 1, 2019): 1184–94. http://dx.doi.org/10.3844/jcssp.2019.1184.1194.

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Vieira, M. C., S. Cope, and J. P. Jansen. "Network meta-analysis of longitudinal data." Value in Health 16, no. 3 (May 2013): A15. http://dx.doi.org/10.1016/j.jval.2013.03.091.

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Daya, Salim. "Meta-analysis using individual patient data." Evidence-based Obstetrics & Gynecology 5, no. 2 (June 2003): 57–59. http://dx.doi.org/10.1016/s1361-259x(03)00090-4.

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Kelley, George A. "Individual Participant Data Meta-Analysis Explained." Journal of Pediatrics 207 (April 2019): 265–66. http://dx.doi.org/10.1016/j.jpeds.2018.12.046.

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Lopez-Lee, David. "Indiscriminate Data Aggregations in Meta-Analysis." Evaluation Review 26, no. 5 (October 2002): 520–44. http://dx.doi.org/10.1177/019384102236522.

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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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Books on the topic "Meta-data-analysis"

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Böhning, Dankmar. Meta-analysis of binary data using profile likelihood. Boca Raton: CRC Press, 2008.

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Meta-analysis of controlled clinical trials. Chichester: John Wiley & Sons, 2002.

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Mullen, Brian. Advanced BASIC meta-analysis. 2nd ed. Mahwah, NJ: Lawrence Erlbaum, 2003.

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Advanced BASIC meta-analysis. Hillsdale, N.J: L. Erlbaum Associates, 1989.

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Guido, Knapp, and Sinha Bimal K. 1946-, eds. Statistical meta-analysis with applications. Hoboken, N.J: Wiley, 2008.

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Böhning, Dankmar. Computer-assisted analysis of mixtures and applications: Meta-analysis, disease mapping and others. Boca Raton, Fla: Chapman & Hall/CRC, 2000.

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1933-, Rosenthal Robert, ed. BASIC meta-analysis: Procedures and programs. Hillsdale, N.J: L. Earlbaum Associates, 1985.

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Computer-assisted analysis of mixtures and applications: Meta-analysis, disease mapping, and others. Boca Raton, Fla: Chapman & Hall/CRC, 1999.

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Wang, Morgan C. Integrating results through meta-analytic review using SAS® software. Cary, NC: SAS Institute, 1999.

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HARMA Meeting (7th 1996 Dublin, Ireland). Meta-analysis and the design and the analysis of multi-site investigations and data sources and information networks in agriculture: VII HARMA Meeting, Dublin, November 8 1996. Dublin: [UCD], 1996.

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Book chapters on the topic "Meta-data-analysis"

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Edwards, Mark G. "Meta-Data-Analysis." In Encyclopedia of Quality of Life and Well-Being Research, 4004–7. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3376.

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Stewart, Lesley, and Mark Simmonds. "Individual Participant Data Meta-Analysis." In Handbook of Meta-Analysis, 151–62. First edition. | Boca Raton : Taylor and Francis, [2020] | Series: Chapman & Hall/CRC handbooks of modern statistical methods: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315119403-8.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Meta-analysis of Continuous Data." In Clinical Data Analysis on a Pocket Calculator, 181–84. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27104-0_32.

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Schwarzer, Guido, James R. Carpenter, and Gerta Rücker. "Missing Data in Meta-Analysis." In Use R!, 143–64. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21416-0_6.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Meta-Analysis of Continuous Data." In Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2, 61–62. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4704-3_17.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Meta-Analysis of Binary Data." In Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2, 63–64. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4704-3_18.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Meta-analysis of Binary Data." In Clinical Data Analysis on a Pocket Calculator, 307–11. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-27104-0_57.

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Saso, Srdjan, Jayanta Chatterjee, Ektoras Georgiou, Sadaf Ghaem-Maghami, Thanos Athanasiou, and Angeles Alvarez-Secord. "Meta-analysis of survival data." In An Atlas of Gynecologic Oncology, 301–16. Fourth edition. | Boca Raton, FL: CRC Press/Taylor & Francis Group, [2018]: CRC Press, 2018. http://dx.doi.org/10.1201/9781351141680-39.

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Hanji, Mallikarjun B. "Individual Patient Data Meta-Analysis." In Meta-Analysis in Psychiatry Research, 105–9. Toronto ; New Jersey : Apple Academic Press, 2017.: Apple Academic Press, 2017. http://dx.doi.org/10.4324/9781315366234-12.

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Pyne, Saumyadipta, Steve Skiena, and Bruce Futcher. "Meta-Analysis of Microarray Data." In Bioinformatics Algorithms, 329–52. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2007. http://dx.doi.org/10.1002/9780470253441.ch15.

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Conference papers on the topic "Meta-data-analysis"

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Chawla, Manisha, and Krishna P. Miyapuram. "Meta-analysis of functional neuroimaging data." In 2013 IEEE Second International Conference on Image Information Processing (ICIIP). IEEE, 2013. http://dx.doi.org/10.1109/iciip.2013.6707594.

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Xie, Yuantao, and Juan Yang. "Improved meta-analysis for truncated data." In 2010 3rd International Conference on Biomedical Engineering and Informatics (BMEI). IEEE, 2010. http://dx.doi.org/10.1109/bmei.2010.5639358.

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Hayashi, Teruaki, and Yukio Ohsawa. "Meta-data generation of analysis tools and connection with structured meta-data of datasets." In 2016 3rd International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2016. http://dx.doi.org/10.1109/spin.2016.7566693.

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Tang, Charles, Andrew Tang, Edward Lee, and Lixin Tao. "Mitigating HTTP Flooding Attacks with Meta-data Analysis." In 2015 IEEE 17th International Conference on High-Performance Computing and Communications; 2015 IEEE 7th International Symposium on Cyberspace Safety and Security; and 2015 IEEE 12th International Conference on Embedded Software and Systems. IEEE, 2015. http://dx.doi.org/10.1109/hpcc-css-icess.2015.203.

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Mair, C. "Making software cost data available for meta-analysis." In "8th Internation Conference on Empirical Assessment in Software Engineering (EASE 2004)" Workshop - 26th International Conference on Software Engineering. IEE, 2004. http://dx.doi.org/10.1049/ic:20040397.

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Kazmi, Saira Ali, Yoo-Ah Kim, Baikang Pei, Nori Ravi, David W. Rowe, Hsin-Wei Wang, Alan Wong, and Dong-Guk Shin. "Meta Analysis of Microarray Data Using Gene Regulation Pathways." In 2008 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2008. http://dx.doi.org/10.1109/bibm.2008.32.

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SUBBAIAH, PERLA, AVISHEK MALLICK, and TUSAR K. DESAI. "META ANALYSIS OF BINARY OUTCOMES DATA IN CLINICAL TRIALS." In Proceedings of Statistics 2011 Canada/IMST 2011-FIM XX. WORLD SCIENTIFIC, 2013. http://dx.doi.org/10.1142/9789814417983_0017.

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Maheeshanake, S. D. L. H., M. W. A. C. R. Wijesinghe, A. R. Weerasinghe, and M. A. I. Perera. "Unsupervised Techniques for Meta-Analysis of Cancer Genomic Data." In 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer). IEEE, 2020. http://dx.doi.org/10.1109/icter51097.2020.9325475.

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David Strang, Kenneth, and Zhaohao Sun. "Meta-analysis of big data security and privacy: Scholarly literature gaps." In 2016 IEEE International Conference on Big Data (Big Data). IEEE, 2016. http://dx.doi.org/10.1109/bigdata.2016.7841101.

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Delgado, Héctor, Massimiliano Todisco, Md Sahidullah, Nicholas Evans, Tomi Kinnunen, Kong Aik Lee, and Junichi Yamagishi. "ASVspoof 2017 Version 2.0: meta-data analysis and baseline enhancements." In Odyssey 2018 The Speaker and Language Recognition Workshop. ISCA: ISCA, 2018. http://dx.doi.org/10.21437/odyssey.2018-42.

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Reports on the topic "Meta-data-analysis"

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Dickersin, Kay, Tianjing Li, and Evan Mayo-Wilson. Integrating Multiple Data Sources for Meta-analysis to Improve Patient-Centered Outcomes Research. Patient-Centered Outcomes Research Institute (PCORI), March 2018. http://dx.doi.org/10.25302/3.2018.me.13035785.

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He, Lin, Dongjie He, Yuhong Qi, Jiejing Zhou, Canliang Yuan, Hao Chang, Qiming Wang, Gaiyan Li, and Qiuju Shao. Stereotactic biopsy for brainstem lesions: A meta-analysis with non-comparative binary data. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2021. http://dx.doi.org/10.37766/inplasy2021.9.0034.

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Hulsegge, Ina, Henri Woelders, Annemarie Rebel, Mari Smits, and Dirkjan Schokker. Meta-analysis of temporal intestinal gene expression data to generate reference profiles: VDI-10. Wageningen: Wageningen Livestock Research, 2017. http://dx.doi.org/10.18174/426338.

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Teng, Cheong Lieng, Verna Kar Mun Lee, Malanashita Ganeson, Lokman Hakim Sulaiman, and Mohamad Adam Bujang. Diabetes self care in Malaysia: protocol of an individual participant data meta-analysis of SDSCA studies. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, January 2021. http://dx.doi.org/10.37766/inplasy2021.1.0090.

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Liu, Baiyan, Bing Yan, Hailin Jiang, Xuewei Zhao, Luyao Wang, Tie Li, and Fuchun Wang. The effectiveness of herbal acupoint application for functional diarrhea Protocol for a meta-analysis and data mining. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, July 2021. http://dx.doi.org/10.37766/inplasy2021.7.0094.

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Nitta, Katsumi. Development of Meta Level Communication Analysis using Temporal Data Crystallization and Its Application to Multi Modal Human Communication. Fort Belvoir, VA: Defense Technical Information Center, July 2013. http://dx.doi.org/10.21236/ada587634.

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Xue, Dan, Zhujin Song, Yuhui Zhang, Xiao Jie, and Aisong Zhu. Efficacy and Safety of Tonic Traditional Chinese Medicine in the Treatment of Depression : A Meta-Analysis and Data Mining. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, September 2021. http://dx.doi.org/10.37766/inplasy2021.9.0068.

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Liu, Yanze, Lin Yao, Fuchun Wang, Bing Yan, Jiazhen Cao, Xiaona Liu, Lijuan Ha, et al. A Protocol for Effectiveness of Acupoint Application of Traditional Chinese Medicine in Treating Primary Dysmenorrhea : Meta-analysis and Data Mining. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, March 2021. http://dx.doi.org/10.37766/inplasy2021.3.0011.

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Nelson, Gena. A Systematic Review of the Quality of Reporting in Mathematics Meta-Analyses for Students with or at Risk of Disabilities Coding Protocol. Boise State University, July 2021. http://dx.doi.org/10.18122/sped138.boisestate.

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Abstract:

The purpose of this document is to provide readers with the coding protocol that authors used to code 22 meta-analyses focused on mathematics interventions for students with or at-risk of disabilities. The purpose of the systematic review was to evaluate reporting quality in meta-analyses focused on mathematics interventions for students with or at risk of disabilities. To identify meta-analyses for inclusion, we considered peer-reviewed literature published between 2000 and 2020; we searched five education-focused electronic databases, scanned the table of contents of six special education journals, reviewed the curriculum vitae of researchers who frequently publish meta-analyses in mathematics and special education, and scanned the reference lists of meta-analyses that met inclusion criteria. To be included in this systematic review, meta-analyses must have reported on the effectiveness of mathematics-focused interventions, provided a summary effect for a mathematics outcome variable, and included school-aged participants with or at risk of having a disability. We identified 22 meta-analyses for inclusion. We coded each meta-analysis for 53 quality indicators (QIs) across eight categories based on recommendations from Talbott et al. (2018). Overall, the meta-analyses met 61% of QIs and results indicated that meta-analyses most frequently met QIs related to providing a clear purpose (95%) and data analysis plan (77%), whereas meta-analyses typically met fewer QIs related to describing participants (39%) and explaining the abstract screening process (48%). We discuss the variation in QI scores within and across the quality categories and provide recommendations for future researchers so that reporting in meta-analyses may be enhanced. Limitations of the current study are that grey literature was not considered for inclusion and that only meta-analyses were included; this limits the generalizability of the results to other research syntheses (e.g., narrative reviews, systematic reviews) and publication types (e.g., dissertations).

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Xing, Lei, Hongmin Guo, and Zhiqian Wang. Efficacy and safety of Suzi Jiangqi Decoction in patients with acute exacerbation of chronic obstructive pulmonary disease A protocol for systematic review and meta analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, August 2021. http://dx.doi.org/10.37766/inplasy2021.8.0035.

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Background: Chronic obstructive pulmonary disease (COPD) is characterized by chronic respiratory symptoms. The respiratory symptoms of patients with acute exacerbation of COPD (AECOPD) worsen rapidly. At present, traditional western medicine treatment can not effectively alleviate the symptoms and attack frequency of patients. Suzi Jiangqi decoction(SZJQ) has a good clinical effect in the treatment of AECOPD. Due to the lack of evidence-based medicine, it can not provide an effective systematic evaluation for the treatment of AECOPD with Suzi Jiangqi decoction. Therefore, it is necessary to provide high-quality evidence evaluation for the clinical efficacy and safety of Suzi Jiangqi Decoction in the treatment of AECOPD. Methods: Two researchers independently retrieved randomized controlled trial (RCT) and quasi-RCTs of SZJQ in the treatment of AECOPD from databases including PubMed, Web of science, the Cochrane Library, CBM, CNKI, Sinomed, VIP and WanFang.The included studies were evaluated for quality according to the RCT quality assessment method provided by Cochrane Reviewer's Handbook 5.3.Review Manager 5.3 software provided by the Cochrane collaboration was used for meta-analysis. Results: This study will provide systematic review on the efficacy and safety of SZJQ as adjuvant therapy in patients with AECOPD by rigorous quality assessment and reasonable data synthesis. Conclusions: This systematic review will provide the good evidence currently on SZJQ as adjuvant therapy in patients with AECOPD.

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