In order to circumvent the influence of correlation in paired-samples and repeated measures experimental designs, researchers typically perform a one-sample Student "t" test on difference scores. That procedure entails some loss of power, because it employs N - 1 degrees of freedom instead of the 2N - 2 degrees of freedom of the…

A computer program randomly sampled ordered pairs of scores from known populations that departed from bivariate normal form and calculated correlation coefficients from sample values. Hypotheses were tested (1) that population correlations are zero using the t statistic; and (2) that population correlations have non-zero values using the r to z…

A computer simulation compared significance tests of correlation coefficients calculated from initial scores, from ranks assigned by the Spearman method, and from three kinds of modified ranks. Implications of findings for the idea that rank correlation is a nonparametric correlation method are discussed. (SLD)

D. W. Zimmerman argues that the interpretation by J. D. Gibbons and S. Chakraborti of recent simulation results and their recommendations are misleading and suggests use of an alternate test when homogeneity of variance and normality are violated. Gibbons and Chakraborti review their differences with Zimmerman's position. (SLD)

Some of the methods originally used to find relationships between reliability and power associated with a single measurement are extended to difference scores. Results, based on explicit power calculations, show that augmenting the reliability of measurement by reducing error score variance can make significance tests of difference more powerful.…

A program obtained random samples from known populations, some of which violated the homogeneity assumption. Student t tests and Mann-Whitney U Tests were performed on the sample value. Where the t test led to incorrect decisions, the use of Mann-Whitney U test in its place led to poorer results. (JAZ)