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

Stat Med. 2002 Jun 15;21(11):1513-24. doi: 10.1002/sim.1184.


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 Using data from a study of publication bias (39 meta-analyses, 394 published and 88 unpublished trials) and language bias (29 meta-analyses, 297 English language trials and 52 non-English language trials), we compare results from logistic regression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

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bias*
  • Epidemiologic Methods
  • Humans
  • Logistic Models
  • Meta-Analysis as Topic*
  • Research Design / standards*
  • Statistics as Topic / methods*
  • Statistics as Topic / standards
  • Treatment Outcome