In the current volume he draws on his experience teaching meta-analysis to thousands of researchers as well as his experience as a reviewer of meta-analyses for numerous journals. 214 Meta-analysis of diagnostic accuracy 3 Models for meta-analysis of diagnostic accuracy Several statistical methods for meta-analysis of data from diagnostic test accuracy stud-ies have been proposed that account for the correlation between sensitivity and speci-city (Moses, Shapiro, and Littenberg 1993 Rutter and Gatsonis 2001 Reitsma. Use of the confidence interval can lend insight into the precision of the treatment estimates. The book’s author is the co-author of the text Introduction to Meta-Analysis, the best-selling text in this field. We describe what meta-analysis is, what heterogeneity is. These examples can serve as templates for reporting an analysis, while avoiding the mistakes discussed in earlier chapters.
COMPREHENSIVE META ANALYSIS ACCURACY HOW TO
The book includes a section with examples that show how to report the results of an analysis correctly. Carvalho and others published Screening for bipolar spectrum disorders: A comprehensive meta-analysis of accuracy studies Find, read and cite all the. Gain analysis of CQT outcomes representing the median accuracy showed a.
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The examples show the real-world consequences of the mistakes, explaining (for example) how the mistakes can lead to the adoption of interventions that may actually be harmful in some populations. We conducted a metaanalysis on the most commonly used forensic polygraph test. Important issues that need to be considered when appraising a systematic. Haitao Chu, Department of Biostatistics and Lineberger Comprehensive. The problems associated with traditional narrative reviews are discussed, as is the role of systematic reviews in limiting bias associated with the assembly, critical appraisal, and synthesis of studies addressing specific clinical questions. In a recent meta-analysis of the accuracy of microsatellite instability testing.
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The book is intended primarily for researchers, and so the discussion is conceptual rather than statistical. This review covers the basic principles of systematic reviews and meta-analyses. For each, it explains why it is a mistake, the implications of the mistake, and how to avoid the mistake. This book outlines the most common mistakes, using examples in medicine, epidemiology, education, psychology, criminal justice, and other fields.
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Among the thousands of meta-analyses that have been published over the past several decades, there are a number of mistakes that appear on a fairly regular basis.