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Kenward-Roger--Type Corrections for Inference Methods of Network Meta-Analysis and Meta-Regression
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Noma, Hisashi; Hamura, Yasuyuki; Gosho, Masahiko; Furukawa, Toshi A. – Research Synthesis Methods, 2023
Network meta-analysis has been an essential methodology of systematic reviews for comparative effectiveness research. The restricted maximum likelihood (REML) method is one of the current standard inference methods for multivariate, contrast-based meta-analysis models, but recent studies have revealed the resultant confidence intervals of average…
Descriptors: Network Analysis, Meta Analysis, Regression (Statistics), Error of Measurement
Calculating the Power of a Planned Individual Participant Data Meta-Analysis of Randomised Trials to Examine a Treatment-Covariate Interaction with a Time-to-Event Outcome
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Riley, Richard D.; Collins, Gary S.; Hattle, Miriam; Whittle, Rebecca; Ensor, Joie – Research Synthesis Methods, 2023
Before embarking on an individual participant data meta-analysis (IPDMA) project, researchers should consider the power of their planned IPDMA conditional on the studies promising their IPD and their characteristics. Such power estimates help inform whether the IPDMA project is worth the time and funding investment, before IPD are collected. Here,…
Descriptors: Computation, Meta Analysis, Participant Characteristics, Data
A Simple Method to Estimate Prediction Intervals and Predictive Distributions: Summarizing Meta-Analyses beyond Means and Confidence Intervals
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Wang, Chia-Chun; Lee, Wen-Chung – Research Synthesis Methods, 2019
A systematic review and meta-analysis is an important step in evidence synthesis. The current paradigm for meta-analyses requires a presentation of the means under a random-effects model; however, a mean with a confidence interval provides an incomplete summary of the underlying heterogeneity in meta-analysis. Prediction intervals show the range…
Descriptors: Meta Analysis, Computation, Statistical Analysis, Prediction
Interpreting Average Effect Sizes: Never a Center without a Spread
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Guskey, Thomas R. – NASSP Bulletin, 2019
School leaders today are making important decisions regarding education innovations based on published average effect sizes, even though few understand exactly how effect sizes are calculated or what they mean. This article explains how average effect sizes are determined in meta-analyses and the importance of including measures of variability…
Descriptors: Effect Size, Educational Innovation, Meta Analysis, Statistical Distributions
Methods for Resampling Meta-Analyses with Multiple Effect Sizes.
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Stewart, Robert Grisham – 2002
During the 1990s, the use of meta-analytic methods in educational research has been widespread, and few aspects of education have escaped the meta-analytic revolution. The acceptance has not been complete, however, and several threats to validity remain. Prominent among these are the "normality" problem and the "independence"…
Descriptors: Educational Research, Effect Size, Meta Analysis, Statistical Distributions
A Primer on the Understanding, Use, and Calculation of Confidence Intervals That Are Based on Central and Noncentral Distributions.
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Cumming, Geoff; Finch, Sue – Educational and Psychological Measurement, 2001
Discusses four reasons for promoting the use of confidence intervals: (1) ease of interpretation; (2) links with familiar statistical tests; (3) promotion of meta-analytic thinking; and (4) increase of information about precision. Discusses calculations of confidence intervals for a basic standardized effect size measure and discusses software for…
Descriptors: Computer Software, Effect Size, Meta Analysis, Research Reports