Latent class analysis (LCA) refers to techniques for identifying groups in data based on a parametric model. Examples include mixture models, LCA with ordinal indicators, and latent class growth analysis. Despite its popularity, there is limited guidance with respect to decisions that must be made when conducting and reporting LCA. Moreover, there…

JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…

It is necessary to test for equivalence of measurements across groups to guarantee that comparisons of regression coefficients or mean scores of a latent factor are meaningful. Unfortunately, when tested, many scales display nonequivalence. Several researchers have suggested that nonequivalence may be used as a useful source of information as to…

Seeking to assess the analytical rigor of empirical research in management education, this article reviews the use of multivariate statistical techniques in 85 studies of online and blended management education over the past decade and compares them with prescriptions offered by both the organization studies and educational research communities.…

Despite the recent increase of structural equation modeling (SEM) in language testing and learning research and Kunnan's (1998) call for the proper use of SEM to produce useful findings, there seem to be no reviews about how SEM is applied in these areas or about the extent to which the current application accords with appropriate practices. To…

In longitudinal studies, investigators often measure multiple variables at multiple time points and are interested in investigating individual differences in patterns of change on those variables. Furthermore, in behavioral, social, psychological, and medical research, investigators often deal with latent variables that cannot be observed directly…

Cluster sampling results in response variable variation both among respondents (i.e., within-cluster or Level 1) and among clusters (i.e., between-cluster or Level 2). Properly modeling within- and between-cluster variation could be of substantive interest in numerous settings, but applied researchers typically test only within-cluster (i.e.,…

The present study explores the validity of a recent stages of change (SoC) measure and algorithm among a sample of late adolescents. MANOVA and structural equation modeling are used to assess the relationship between five SoC groups (precontemplation, contemplation, preparation, action, and maintenance) and a set of dependent measures including…

This study examined the association between prenatal exposure to cocaine and physiological regulation across the first 7 months of age. Measures of respiratory sinus arrhythmia (RSA) were obtained from 169 (82 cocaine-exposed and 87 nonexposed) infants during baseline periods at 1 month and 7 months of age and during tasks designed to elicit…

When assessing latent mean differences, researchers frequently do not explore possible heterogeneity within their data sets. Sources of differences may be functions of a nested data structure or heterogeneity in the form of unobserved classes of observations defined by a difference in factor means. In this study, the use of multilevel structural…

A correlation structure modeling method for comparison of mediated effects is outlined. The procedure permits point and interval estimation of differences in mediator effects, and is useful with models postulating 1 or more predictor, intervening, or response variables that may also be latent constructs. The approach allows scale-free evaluation…

In this investigation, we used a classic latent profile analysis (LPA), a person-centered approach, to identify groups of students who had similar profiles for multiple dimensions of academic self-concept (ASC) and related these LPA groups to a diverse set of correlates. Consistent with a priori predictions, we identified 5 LPA groups representing…

This study examines the growth and development of structural equation modeling (SEM) from the years 1994 to 2001. The synchronous development and growth of the Structural Equation Modeling journal was also examined. Abstracts located on PsycINFO were used as the primary source of data. The major results of this investigation were clear: (a) The…

This paper presents a discussion of various statistical concepts and techniques in light of two propositions. The first is that researchers need to select analytical techniques that prevent them from committing Type VI errors, which are inconsistencies between the research question and the statistical analysis. The second is that many statistical…

Since data in social and behavioral sciences are often hierarchically organized, special statistical procedures for covariance structure models have been developed to reflect such hierarchical structures. Most of these developments are based on a multivariate normality distribution assumption, which may not be realistic for practical data. It is…