The basic assumption of Cooper's nonparametric test for trend (EJ 125 069) is questioned. It is contended that the proper assumption alters the distribution of the statistic and reduces its usefulness. (JKS)

Analyses of artificial data involving repeated, related binary measures to different samples suggest that Tideman's generalized chi-square statistic and conventional repeated-measures analysis of variance do not produce conflicting outcomes. Provided the appropriate assumptions are met, analysis of variance may provide a more versatile approach.…

It is argued here that the choice of the appropriate method for calculating least squares analysis of variance with unequal sample sizes depends upon the question the experimenter wants to answer about the data. The different questions reflect different null hypotheses. An example is presented using two alternative methods. (Author/BW)

Post-hoc blocking and analysis of covariance (ANCOVA) both employ a concomitant variable to increase statistical power relative to the completely randomized design. It is argued that the advantages attributed to the block design are not always valid and that there are circumstances when the ANCOVA would be preferred to post-hoc blocking.…

When reporting results, researchers must not change predetermined significance levels. Such attempts to make results more significant are statistically inaccurate, illogical, and unethical. American Psychological Association standards for reporting significance should be more explicit. (CP)

Makes the case that science is best served when researchers focus on the size of effects and their practical significance. Advocates the use of confidence intervals for deciding whether chance or sampling variability is an unlikely explanation for an observed effect. Calls for more emphasis on effect sizes in the next edition of the American…