A model-based framework, due originally to R. A. Fisher, and a design-based framework, due originally to J. Neyman, offer alternative mechanisms for inference from samples to populations. We show how these frameworks can utilize different types of samples (nonrandom or random vs. only random) and allow different kinds of inference (descriptive vs.…

Dominance analysis (Budescu, 1993) offers a general framework for determination of relative importance of predictors in univariate and multivariate multiple regression models. This approach relies on pairwise comparisons of the contribution of predictors in all relevant subset models. In this article we extend dominance analysis to canonical…

Evaluating the fit of a structural equation model via bootstrap requires a transformation of the data so that the null hypothesis holds exactly in the sample. For complete data, such a transformation was proposed by Beran and Srivastava (1985) for general covariance structure models and applied to structural equation modeling by Bollen and Stine…

Developed a sample-based nonanalytical degrees-of-freedom correction factor for situations sampling both subjects and conditions with measurement data departing from essentially parallel form. Assessed the application of this correction factor through a simulation study involving data sets with a range of design characteristics and manifesting…

The finite intersection test (FIT) developed by P. K. Krishnaiah (1964, 1965) is discussed and compared with more familiar methods for simultaneous inference. How the FIT can be used to analyze differences among all means for both univariate and multivariate experimental designs is explained. (SLD)

Theoretical nonparametric conditions under which evidence from salary studies using observed merit measures can provide a basis for inferences of fairness are discussed. Latent variable models as parametric special cases of the general conditions presented are illustrated with real salary data. Implications for empirical studies of salary equity…

Limitations of dummy coding and nonsense coding as methods of coding categorical variables for use as predictors in multiple regression analysis are discussed. The combination of these approaches often yields estimates and tests of significance that are not intended by researchers for inclusion in their models. (SLD)

Investigated the validity of inferences from A. Jensen's method of studying group differences on cognitive tests (1985) and compared the validity of inferences to inferences based on multi-group confirmatory factor analysis using constructed population covariance matrices. Results show the insensitivity of Jensen's method and the superiority of…

Mardia's measure of multivariate kurtosis has been implemented in many statistical packages commonly used by social scientists. It provides important information on whether a commonly used multivariate procedure is appropriate for inference. Many statistical packages also have options for missing data. However, there is no procedure for applying…

Variance formulas of H. E. Daniels and M. G. Kendall (1947) are generalized to allow for the presence of ties and variance of the sample tau correlation. Applications of these generalized formulas are discussed and illustrated using data from a 1965 study of contraceptive use in 15 developing countries. (SLD)