Meta-regression methods for detecting and estimating empirical effects in the presence of publication selection

This study investigates the small-sample performance of meta-regression methods for detecting and estimating genuine empirical effects in research literatures tainted by publication selection. Publication selection exists when editors, reviewers or researchers have a preference for statistically significant results. Meta-regression methods are found to be robust against publication selection. Even if a literature is dominated by large and unknown misspecification biases, precision-effect testing and joint precision-effect/meta-significance testing can provide viable strategies for detecting genuine empirical effects. Publication biases are greatly reduced by combining two biased estimates, the estimated meta-regression coefficient on precision (1/Se) and the unadjusted average effect.