Publication and selection biases in meta-analysis are more likely to affect small studies, which also tend to be of lower methodological quality. This may lead to "small-study effects," where the smaller studies in a meta-analysis show larger treatment effects. Small-study effects may also arise because of between-trial heterogeneity. Statistical tests for small-study effects have been proposed, but their validity has been questioned. A set of typical meta-analyses containing 5, 10, 20, and 30 trials was defined based on the characteristics of 78 published meta-analyses identified in a hand search of eight journals from 1993 to 1997. Simulations were performed to assess the power of a weighted regression method and a rank correlation test in the presence of no bias, moderate bias or severe bias. We based evidence of small-study effects on P
Regression Analysis
,Statistics, Nonparametric
,Reproducibility of Results
,Publication Bias
,Clinical Trials as Topic
,Statistics as Topic
,Meta-Analysis as Topic
,Bias