Estimates of heterogeneity (I2) can be biased in small meta-analyses
classification
📊 stat.ME
keywords
estimatesheterogeneitymeta-analysissmallbiasedmeta-analysesstudieswhen
read the original abstract
In meta-analysis, the fraction of variance that is due to heterogeneity is known as I2. We show that the usual estimator of I2 is biased. The bias is largest when a meta-analysis has few studies and little heterogeneity. For example, with 7 studies and the true value of I2 at 0, the average estimate of I2 is .124. Estimates of I2 should be interpreted cautiously when the meta-analysis is small and the null hypothesis of homogeneity (I2=0) has not been rejected. In small meta-analyses, confidence intervals may be preferable to point estimates for I2.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.