When a self-report instrument includes a balanced number of positively and negatively worded items, factor analysts often use method factors to aid model fitting. The nature of these factors, often referred to as acquiescence, is still debated. Relying upon previous results (Alessandri et al., 2010; DiStefano & Motl, 2006, 2008; Rauch, Schweizer,…

Diagnostic scores are of increasing interest in educational testing due to their potential remedial and instructional benefit. Naturally, the number of educational tests that report diagnostic scores is on the rise, as are the number of research publications on such scores. This article provides a critical evaluation of diagnostic score reporting…

The noncentral chi-square approximation of the distribution of the likelihood ratio (LR) test statistic is a critical part of the methodology in structural equation modeling. Recently, it was argued by some authors that in certain situations normal distributions may give a better approximation of the distribution of the LR test statistic. The main…

This article provides the theory and application of the 2-stage maximum likelihood (ML) procedure for structural equation modeling (SEM) with missing data. The validity of this procedure does not require the assumption of a normally distributed population. When the population is normally distributed and all missing data are missing at random…

Double cross-validation of a test battery against multiple criterion variables found the first general factor accounts for most criterion variance in cross-validated regression weights. Small contributions are made by mechanical/technical and psychomotor factors. It appears a common general factor plays the major role in validity for a range of…

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Evaluated a cross-validation approach for cluster analyses through two simulation studies. Although on the average replication indices peaked in the region of the true number of clusters, choosing the number of clusters by maximum replication results in a negatively biased estimate. Using a "scree test" to attenuate this bias is…

The construct validity of the cognitive, affective, and behavioral components of attitudes were investigated via the analysis of covariance structures method. Results are interpreted from a cognitive consistency and learning theory perspective. (Author/JKS)

There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants…

Presents a simple method for generating simulated plasmodes and artificial test clusters with user-defined shape, size, and orientation. For "J" clusters, indicator validity is defined as the squared correlation ratio between the cluster indicator and J-1 dummy variables. Illustrates the method through simulation. (SLD)

A linear combination of a set of measures is often sought as an overall score summarizing subject performance. The weights in this composite can be selected to maximize its reliability or to maximize its validity, and the optimal choice of weights is in general not the same for these two optimality criteria. We explore several relationships…

Three potential applications of stepwise procedures in canonical analysis and several alternative stepping decision rules are described. Results of an empirical investigation of the procedures indicated that more parsimonious approaches to maintaining variables held up better under cross-validation. (Author/JKS)

Monte Carlo validation studies of clustering algorithms, including Ward's minimum variance hierarchical method, are reviewed. Caution concerning the uncritical selection of Ward's method for recovering cluster structure is advised. Alternative explanations for differential recovery performance are explored and recommendations are made for future…

Results of empirical comparisons of an inferential model of order analysis with factor analytic models were reported for two sets of data. On the prestructured data set both order and factor analytic models returned its dimensions of length, width and height, but on the random data set the factor analytic models indicated the presence of…

Twenty-three different methods of cluster analysis were compared in a four-stage sequential validation design. Results demonstrated that the solution given by Ward's method of cluster analysis was particularly powerful in comparison to solutions yielded by other techniques. (Author/JKS)