Longitudinal models provide researchers with a framework for investigating key aspects of change over time, but rarely is "time" itself modeled as a focal parameter of interest. Rather than treat time as purely an index of measurement occasions, the proposed Time to Criterion (T2C) growth model allows for modeling individual variability…

In this ITEMS module, we frame the topic of scale reliability within a "confirmatory factor analysis" and "structural equation modeling" (SEM) context and address some of the limitations of Cronbach's a. This modeling approach has two major advantages: (1) it allows researchers to make explicit the relation between their items…

Structured means analysis is a very useful approach for testing hypotheses about population means on latent constructs. In such models, a z test is most commonly used for testing the statistical significance of the relevant parameter estimates or of the differences between parameter estimates, where a z value is computed based on the asymptotic…

Latent interaction models have motivated a great deal of methodological research, mainly in the area of estimating such models. Product-indicator methods have been shown to be competitive with other methods of estimation in terms of parameter bias and standard error accuracy, and their continued popularity in empirical studies is due, in part, to…

Although classical statistical techniques have been a valuable tool in second language (L2) research, L2 research questions have started to grow beyond those techniques' capabilities, and indeed are often limited by them. Questions about how complex constructs relate to each other or to constituent subskills, about longitudinal development in…

A two-step process is commonly used to evaluate data-model fit of latent variable path models, the first step addressing the measurement portion of the model and the second addressing the structural portion of the model. Unfortunately, even if the fit of the measurement portion of the model is perfect, the ability to assess the fit within the…

This study proposes robust means modeling (RMM) approaches for hypothesis testing of mean differences for between-subjects designs in order to control the biasing effects of nonnormality and variance inequality. Drawing from structural equation modeling (SEM), the RMM approaches make no assumption of variance homogeneity and employ robust…

Valuable methods have been developed for incorporating ordinal variables into structural equation models using a latent response variable formulation. However, some model parameters, such as the means and variances of latent factors, can be quite difficult to interpret because the latent response variables have an arbitrary metric. This limitation…

Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…

An adaptation of the Family Stress Model was examined using structural equation modeling with data from 193 custodial grandmother-grandfather dyads. The model's measurement and structural components were largely invariant by grandparent gender. For grandmothers and grandfathers alike, the effects of their psychological and marital distress on…

As Rupp and Templin (2008) stated directly, diagnostic classification methods "are confirmatory in nature." Methods, though, are neither inherently confirmatory nor exploratory. Diagnostic classification modeling, with its analytical and computational obstacles eventually yielding as a comprehensive and potent discipline emerges, will…

Proposes an analog to the Scheffe test (H. Scheffe, 1953) to be applied to the exploratory model-modification scenario. The method is a sequential finite-intersection multiple-comparison procedure that controls the Type I error rate to a desired alpha level across all possible post hoc model modifications. (SLD)

The purpose of this validity study was to improve measurement of coaching efficacy, an important variable in models of coaching effectiveness. A revised version of the coaching efficacy scale (CES) was developed for head coaches of high school teams (CES II-HST). Data were collected from head coaches of 14 relevant high school sports (N = 799).…

In its most basic form, latent growth modeling (latent curve analysis) allows an assessment of individuals' change in a measured variable X over time. For simple linear models, as with other growth models, parameter estimates associated with the a construct (amount of X at a chosen temporal reference point) and b construct (growth in X per unit…

This paper illustrates the differences in inference that can be seen when traditional and multilevel structural equation modeling techniques are applied to hierarchical data. Research on faculty is an area in which multilevel data exist, and where previous research generally has not modeled the nested structure. Using data from the National Study…