Bias caused by sampling error in meta-analysis with small sample sizes.

ABSTRACT:

Background

Meta-analyses frequently include studies with small sample sizes. Researchers usually fail to account for sampling error in the reported within-study variances; they model the observed study-specific effect sizes with the within-study variances and treat these sample variances as if they were the true variances. However, this sampling error may be influential when sample sizes are small. This article illustrates that the sampling error may lead to substantial bias in meta-analysis results.

Methods

We conducted extensive simulation studies to assess the bias caused by sampling error. Meta-analyses with continuous and binary outcomes were simulated with various ranges of sample size and extents of heterogeneity. We evaluated the bias and the confidence interval cove

SUBMITTER: Lin L 

PROVIDER: S-EPMC6136825 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature