A previous Monte Carlo study examined the relative powers of several simple and more complex procedures for testing the significance of difference in mean rates of change in a controlled, longitudinal, treatment evaluation study. Results revealed that the relative powers depended on the correlation structure of the simulated repeated measurements.…

A procedure for testing heterogeneity of variance is developed which generalizes readily to complex, multi-factor experimental designs. Monte Carlo studies indicate that the Z-variance test statistic presented here yields results equivalent to other familiar tests for heterogeneity of variance in simple one-way designs where comparisons are…

Describes a computer program for calculating the power of the F-test. Approach is based upon two independent approximations-- a normalization of the non-central F distribution and an integration of the normal distribution. Comparison of the calculated values of power with exact values revealed a high degree of accuracy. (Author/RC)

A specific form of nonrandom assignment to treatment groups, the "alternate ranks" design, was investigated. This design eliminates the possibility of a correlation between the covariate and the treatment, and rules out experimenter bias in assignment of subjects to groups. (Editor)

Formulae for estimating individual rater reliabilities from analysis of treatment effects are presented and evaluated. Monte Carlo methods illustrate the formulae. Results indicate that large sample sizes, large true treatment effects, and large differences in the actual reliabilities of raters are required for the approach to be useful. (SLD)

The following models which provide an estimate of the reliability of a rating scale are described: (1) disattenuation; (2) common factor; (3) external criterion; (4) treatment effects; and (5) regression. Such models are especially useful in selecting, evaluating, and training participants in clinical research. (SLD)