Temporal Dependence and Bias in Meta-Analysis

Abstract

Decisions to undertake bio-medical studies might depend on the results of previous similar studies. So too might the timing of meta-analyses. We show how temporal dependence among the studies analyzed in the meta-analysis, as well as the timing of the meta-analysis itself, can bias the results of the meta-analysis. We show analytically and numerically that a “toy” meta-analysis is biased. We then study bias in a more realistic stochastic process model of meta-analysis. We conclude that in meta-analysis it is difficult of avoid bias that is caused by statistical dependence among studies.

Keywords:

• Clinical trials
• Dependent data
• Stochastic process

Mathematics Subject Classification:

• Primary 62P10
• Secondary 62M09

Acknowledgment

Steven P. Ellis was supported in part by United States Public Health Service grant MH62185.