When selecting a multilevel model to fit to a dataset, it is important to choose both a model that best matches characteristics of the data's structure, but also to include the appropriate fixed and random effects parameters. For example, when researchers analyze clustered data (e.g., students nested within schools), the multilevel model can be…

The notion that there is often no clear distinction between factorial and typological models (von Davier, Naemi, & Roberts, this issue) is sound. As von Davier et al. state, theory often indicates a preference between these models; however the statistical criteria by which these are delineated offer much less clarity. In many ways the procedure…

A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…

One useful and increasingly popular method of classifying students is known commonly as cluster analysis. The variety of techniques that comprise the cluster analytic family are intended to sort observations (for example, students) within a data set into subsets (clusters) that share similar characteristics and differ in meaningful ways from other…

Background: Because of the educational reform and decreasing birth rate in Taiwan over the past 20 years, higher technological and vocational Education (TVE) in Taiwan faces a severe student recruitment competition. Dailey (2007) indicates the need to develop marketing strategies in higher education is evident. TVE institutes are beginning to…

Proposes a Bayesian analysis of the multivariate linear model with polytomous variables. Shows how a Gibbs sampler algorithm is implemented to produce the Bayesian estimates. Illustrates the proposed methodology through examples using multivariate linear regression and multivariate two-way analysis of variance with real data. (SLD)

When selection occurs on the basis of two or more predictors, multivariate restriction of range can reduce various parameters of a validation study. A Statistical Analysis System (SAS) and a Fortran IV program are described that allow for correction of criterion standard deviation(s) and zero-order validities. (Author)

Multivariate selection can be represented as a linear transformation in a geometric framework. In this note this approach is extended to describe the effects of selection on regression analysis and to adjust for the effects of selection using the inverse of the linear transformation. (Author/BW)

Purposes of multivariate analyses are discussed, focusing on the primary purposes of prediction and structure identification and the secondary purpose of response variable ordering. The sound initial choice of response variables and the advisability of simpler analyses when feasible are discussed. (SLD)

Across conditions, differences between population parameters defined by common factor analysis and component analysis are demonstrated. Implications for data analytic and theoretical issues related to choice of analytic model are discussed. Results suggest that principal components analysis should not be used to obtain parameters reflecting latent…

A review of model-selection criteria is presented, suggesting their similarities. Some problems treated by hypothesis tests may be more expeditiously treated by the application of model-selection criteria. Multivariate analysis, cluster analysis, and factor analysis are considered. (Author/GDC)

Effects of different weighting schemes on selecting the optimal number of observations in multivariate-multifacet generalizability designs are studied when cost constraints are imposed. Comparison of four schemes through simulation indicates that all four produce similar optimal values and that reliability should be similar. (SLD)

Purpose: This article reports on a within-family study to identify factors that lead mothers to expect that a particular child will serve in the role of primary caregiver. Design and Methods: Data for this study were collected by in-person interviews with a representative sample of 566 mothers between the ages of 65 and 75 years residing in the…

Cudeck and Browne (1983) proposed using cross-validation as a model selection technique in structural equation modeling. The purpose of this study is to examine the performance of eight cross-validation indices under conditions not yet examined in the relevant literature, such as nonnormality and cross-validation design. The performance of each…

Type I error rates of four multivariate tests (Pilai-Bartlett trace, Johansen's test, James' first-order test, and James' second-order test) were compared for heterogeneous covariance matrices in 360 simulated experiments. The superior performance of Johansen's test and James' second-order test is discussed. (SLD)