Testing the significance of a common risk difference in meta-analysis.

DOI10.1016/S0167-9473(99)00055-9zbMath1061.62564OpenAlexW2016140862MaRDI QIDQ1575216

J. Sánchez-Meca, F. Marín-Martínez

Publication date: 21 August 2000

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0167-9473(99)00055-9

zbMATH Keywords

Meta-analysisType I errorEffect sizeRisk differenceStatistical power

Mathematics Subject Classification ID

Monte Carlo methods (65C05) Contingency tables (62H17) Testing in survival analysis and censored data (62N03)

Related Items (6)

Monitoring the conforming fraction of high-quality processes using a control chart \(p\) under a small sample size and an alternative estimator ⋮ A comparison of some confidence intervals for a binomial proportion based on a shrinkage estimator ⋮ On the Q statistic with constant weights for standardized mean difference ⋮ Testing for Homogeneity in Meta-Analysis I. The One-Parameter Case: Standardized Mean Difference ⋮ Revisiting proportion estimators ⋮ Investigating heterogeneity in meta-analysis of studies with rare events. Estimating the amount of heterogeneity

Uses Software

• GAUSS
• SAS

Cites Work

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• An evaluation of simple methods for the estimation of a common odds ratio in clusters with variable size
• A modified random-effect procedure for combining risk difference in sets of 2×2 tables from clinical trials
• Some Methods for Strengthening the Common χ 2 Tests

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