Temporal Dependence and Bias in Meta-Analysis |
| |
| Authors: | Steven P. Ellis Jonathan W. Stewart |
| |
| Affiliation: | 1. New York State Psychiatric Institute at Columbia University , New York, New York, USA spe4@columbia.edu;3. New York State Psychiatric Institute at Columbia University , New York, New York, USA |
| |
| 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 |
|
|
