Statistical methods for assessing the influence of study characteristics on treatment effects in ‘meta‐epidemiological’ research

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Abstract
Biases in systematic reviews and meta‐analyses may be examined in ‘meta‐epidemiological’ studies, in which the influence of trial characteristics such as measures of study quality on treatment effect estimates is explored. Published studies to date have analysed data from collections of meta‐analyses with binary outcomes, using logistic regression models that assume that there is no between‐ or within‐meta‐analysis heterogeneity. Using data from a study of publication bias (39 meta‐analyses, 394 published and 88 unpublished trials) and language bias (29 meta‐analyses, 297 English language trials and 52 non‐English language trials), we compare results from logistic regression models, with and without robust standard errors to allow for clustering on meta‐analysis, with results using a ‘meta‐meta‐analytic’ approach that can allow for between‐ and within‐meta‐analysis heterogeneity. We also consider how to allow for the confounding effects of different trial characteristics. We show that both within‐ and between meta‐analysis heterogeneity may be of importance in the analysis of meta‐epidemiological studies, and that confounding exists between the effects of publication status and trial quality. Copyright © 2002 John Wiley & Sons, Ltd.
Funding Information
  • U.K. National Health Service Health Technology Assessment Programme (97/18/05)