DARHUBER: a computer program for effect size estimation in linear regression and for calculating the significance of difference between observed and expected R2 values V
DARHUBER: a computer program for effect size estimation in linear regression and for calculating the significance of difference between observed and expected R2 values V

Summary/Abstract: In linear multiple regression it is common practice to test whether the squared multiple correlation coefficient, R2 , differs significantly from zero. Although frequently used, this test is misleading because the expected value of R2 is not zero under the null hypothesis that ρ, the population value of the multiple correlation coefficient, equals zero. The nonzero expected value of R2 has implications both for significance testing and effect size estimation involving the squared multiple correlation coefficient. In this paper we discuss and offer a freely available computer program that calculates the expected value of R2 , an adjusted R2 value and effect size measure that both incorporate the expected value of R2 , and an F statistic that tests the significance of difference between the obtained R2 and the expected value of R2 under the null hypothesis that ρ = 0. The interactive, stand-alone program is written in FORTRAN 77 for a Windows environment. The user simply enters the value of a multiple correlation coefficient from a linear regression, the number of predictors, and the sample size. No knowledge of FORTRAN or any other statistical programming language is required.

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