Evaluation of Statistical Power in Random Effect Meta Analyses for Correlation Effect Size

Abstract

In meta-analysis, numerical index is used as an estimate of effect size to describe the results of each study and thereafter these estimates of across studies are combined to obtain summary of results. 
 It should be known that calculations of the power of statistical tests are important in planning research studies and for interpreting situations in which a result has not proven to be statistically significant. Although statistical power is often considered in the design of primary research studies, it is rarely considered in meta-analysis. Despite the importance of statistical power, few studies have been examined the performance of simulated power in meta-analysis. (In this study, calculations of statistical power for statistical tests that are used for unequal sample size on random effects model in meta-analysis using correlation coefficient as effect size were conducted.)
 The power of the test for the overall effect size was calculated by using both analytical method and simulation method. Thus, it was investigated whether there was any difference between the simulation power and analytical power in random effects meta-analysis by using correlation coefficient as an effect size.