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Michael Borenstein – Research Synthesis Methods, 2024
In any meta-analysis, it is critically important to report the dispersion in effects as well as the mean effect. If an intervention has a moderate clinical impact "on average" we also need to know if the impact is moderate for all relevant populations, or if it varies from trivial in some to major in others. Or indeed, if the…
Descriptors: Meta Analysis, Error Patterns, Statistical Analysis, Intervention
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Brinley N. Zabriskie; Nolan Cole; Jacob Baldauf; Craig Decker – Research Synthesis Methods, 2024
Meta-analyses have become the gold standard for synthesizing evidence from multiple clinical trials, and they are especially useful when outcomes are rare or adverse since individual trials often lack sufficient power to detect a treatment effect. However, when zero events are observed in one or both treatment arms in a trial, commonly used…
Descriptors: Meta Analysis, Error Correction, Computation, Simulation
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Turner, Simon Lee; Korevaar, Elizabeth; Cumpston, Miranda S.; Kanukula, Raju; Forbes, Andrew B.; McKenzie, Joanne E. – Research Synthesis Methods, 2023
Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…
Descriptors: Quasiexperimental Design, Graphs, Accuracy, Computation
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Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction