Generalizations of the Scheffe, Tukey, and Bonferroni-t techniques are presented, each of which controls the experimentwise error rate for a particular type of partially or fully planned analysis. All three procedures provide more power than multivariate analysis of variance (MANOVA) tests. (Author/BJG)

The need for multiple comparison procedures for repeated measures means employing a pooled estimate of error variance to conform to the sphericity assumptions of the design in order to provide a valid test is discussed. An alternative approach which does not require this assumption is presented. (Author/JKS)

Three statistical analysis procedures for analysis of repeated measures data are examined. The procedures are classical mixed model analysis of variance, multivariate analysis of repeated measures, and the analysis of covariance structures. (Author/JKS)

The use of analysis of covariance in simple repeated measures designs is considered. Conditions necessary for the analysis of covariance adjusted main effects and interactions to be meaningful are presented. (Author/JKS)

The partitioned-U procedure is outlined, a fundamental logical flaw in this procedure's avoidance of any direct test of the significance of the first discriminant function or largest coefficient of canonical correlation is pointed out, and two alternatives to the partitioned-U procedure are discussed. (Author/DEP)

Several general correlation patterns are shown which give exact F tests in an analysis of variance (ANOVA) procedure. They are the most general correlation patterns one can assume in a one-way and two-way layout and still have the F tests be valid. (Author/BW)

The relation between the power of a significance test in a block design with correlated measurements and the reliability of the measuring instrument is analyzed in terms of the components of variance entering the reliability coefficient and the noncentrality parameter. (Author/LMO)