Addressing the estimation of standard errors in fixed effects meta-analysis.

Clara Domínguez Islas, Kenneth M Rice

OAI: oai:www.repository.cam.ac.uk:1810/276614 • DOI: 10.17863/CAM.23914

Standard methods for fixed effects meta-analysis assume that standard errors for study-specific estimates are known, not estimated. While the impact of this simplifying assumption has been shown in a few special cases, its general impact is not well understood, nor are general-purpose tools available for inference under more realistic assumptions. In this paper, we aim to elucidate the impact of using estimated standard errors in fixed effects meta-analysis, showing why it does not go away in large samples and quantifying how badly miscalibrated standard inference will be if it is ignored. We also show the important role of a particular measure of heterogeneity in this miscalibration. These developments lead to confidence intervals for fixed effects meta-analysis with improved performance for both location and scale parameters.

fixed effects Heterogeneity Meta-Analysis random effects Biostatistics Common Cold Computer Simulation Humans Meta-Analysis as Topic Models Statistical Systematic Reviews as Topic Zinc