Methods for second order meta-analysis and illustrative applications

This paper presents methods for second order meta-analysis along with several illustrative applications. A second order meta-analysis is a meta-analysis of a number of statistically independent and methodologically comparable first order meta-analyses examining ostensibly the same relationship in different contexts. First order meta-analysis greatly reduces sampling error variance but does not eliminate it. The residual sampling error is called second order sampling error. The purpose of a second order meta-analysis is to estimate the proportion of the variance in mean meta-analytic effect sizes across multiple first order meta-analyses attributable to second order sampling error and to use this information to improve accuracy of estimation for each first order meta-analytic estimate. We present equations and methods based on the random effects model for second order meta-analysis for three situations and three empirical applications of second order meta-analysis to illustrate the potential value of these methods to the pursuit of cumulative knowledge.