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Direct linkKulinskaya, Elena; Hoaglin, David C. – Research Synthesis Methods, 2023
For estimation of heterogeneity variance T[superscript 2] in meta-analysis of log-odds-ratio, we derive new mean- and median-unbiased point estimators and new interval estimators based on a generalized Q statistic, Q[subscript F], in which the weights depend on only the studies' effective sample sizes. We compare them with familiar estimators…
Descriptors: Q Methodology, Statistical Analysis, Meta Analysis, Intervals
Lin, Lifeng – Research Synthesis Methods, 2019
Assessing publication bias is a critical procedure in meta-analyses for rating the synthesized overall evidence. Because statistical tests for publication bias are usually not powerful and only give "P" values that inform either the presence or absence of the bias, examining the asymmetry of funnel plots has been popular to investigate…
Descriptors: Meta Analysis, Sample Size, Graphs, Bias
Li, Xinru; Dusseldorp, Elise; Meulman, Jacqueline J. – Research Synthesis Methods, 2019
In meta-analytic studies, there are often multiple moderators available (eg, study characteristics). In such cases, traditional meta-analysis methods often lack sufficient power to investigate interaction effects between moderators, especially high-order interactions. To overcome this problem, meta-CART was proposed: an approach that applies…
Descriptors: Correlation, Meta Analysis, Identification, Testing
Hong, Sanghyun; Reed, W. Robert – Research Synthesis Methods, 2021
The purpose of this study is to show how Monte Carlo analysis of meta-analytic estimators can be used to select estimators for specific research situations. Our analysis conducts 1620 individual experiments, where each experiment is defined by a unique combination of sample size, effect size, effect size heterogeneity, publication selection…
Descriptors: Monte Carlo Methods, Meta Analysis, Research Methodology, Experiments
Burke, Danielle L.; Ensor, Joie; Snell, Kym I. E.; van der Windt, Danielle; Riley, Richard D. – Research Synthesis Methods, 2018
Percentage study weights in meta-analysis reveal the contribution of each study toward the overall summary results and are especially important when some studies are considered outliers or at high risk of bias. In meta-analyses of test accuracy reviews, such as a bivariate meta-analysis of sensitivity and specificity, the percentage study weights…
Descriptors: Meta Analysis, Research Reports, Statistical Analysis, Sample Size
Veroniki, Areti Angeliki; Pavlides, Marios; Patsopoulos, Nikolaos A.; Salanti, Georgia – Research Synthesis Methods, 2013
A problem that is frequently encountered during the systematic review process is when studies that meet the inclusion criteria do not provide the appropriate numerical estimates to include in a meta-analysis. For dichotomous outcomes, a method has been suggested by Di Pietrantonj for reconstructing the 2 × 2 table when the Odds Ratio…
Descriptors: Meta Analysis, Tables (Data), Statistical Analysis, Error of Measurement
