Statistical methods for assessing the influence of study characteristics on treatment effects in 'meta-epidemiological' research.

Journal article

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 Using data from a study of publication bias (39 meta-analyses, 394 published and 88 unpublished trials) and language bias (29 meta-analyses, 297 English language trials and 52 non-English language trials), we compare results from logistic regression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.

Authors: Sterne, J; Jüni, P; Schulz, K; Altman, D; Bartlett, C

• Publication status: Published
• Journal: Statistics in medicine
• Volume: 21
• Issue: 11
• Pages: 1513-1524
• Publication date: 2002-06-01
• DOI: 10.1002/sim.1184
• EISSN: 1097-0258
• ISSN: 0277-6715
• Language: English
• Keywords: Research Design; Statistics as Topic; Humans; Meta-Analysis as Topic; Treatment Outcome; Epidemiologic Methods; Logistic Models; Bias (Epidemiology)