Functional and structural relationship alternatives to the standard "F"-test for analysis of covariance (ANCOVA) are discussed for cases when the covariate is measured with error. An approximate statistical test based on the functional relationship approach is preferred on the basis of Monte Carlo simulation results. (SLD)

A Monte Carlo Study was conducted to evaluate six models commonly used to evaluate change. The results revealed specific problems with each. Analysis of covariance and analysis of variance of residualized gain scores appeared to substantially and consistently overestimate the change effects. Multiple factor analysis of variance models utilizing…

Results provide a first step toward the establishment of guidelines for the experimenter who wishes to use nonmetric multidimensional scaling effectively, especially when an underlying configuration is hypothesized. (Author)

A large number of correlational models for cross-tabular analysis are available for utilization by social scientists for data description. Criteria for selection (such as levels of measurement and proportional reduction in error) do not lead to conclusive model choice. Moreover, such criteria may be irrelevant. More pertinent criteria are…

The purpose of this study was to compare the results of an analysis of covariance design to a method developed by the authors called within-class regression. Application of this statistical method can be to any quasiexperimental design with a large number of groups. A test of statistical significance to use with the within-class regression…