Nonlinearity of Range Corrections in Meta-Analysis: Test of an Improved Procedure

The authors evaluated an improved procedure for range-restriction corrections in meta-analysis. When population correlations were approximately normally distributed, the new nonlinear rangecorrection procedure improved the accuracy of the Schmidt-Hunter (S-H) interactive method in estimating both the mean (Me) and standard deviation (SDf) of population correlations, making it the most accurate of the procedures examined. In the homogeneous case (SDP = 0), the nonlinear range correction again improves accuracy of estimates ofSDf. In this important case, Taylor Series Approximation (TSA) 1 is considerably less accurate than the S-H interactive and the TSA2 procedures, and N. S. Raju, M. J. Burke, J. Normand, and G. M. Langlois's (1991) procedure yields the least accurate estimates of SDP. Finally, the authors found that the nonlinear range-correction procedure produces improvements in the accuracy of the interactive method even under extreme violations of the normality assumption.