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…

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…

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…

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…

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).…

A simulation study compared three methods of estimating parameters within structural equation models (SEM) with polytomous variables. These methods appear in three SEM computer software packages: (1) LISREL (Joreskog and Sorbom, 1996) with PRELIS (Joreskog and Sorbom); (2) EQS (Bentler, 1995); and (3) the new Mplus (Muthen and Muthen, 1998). The…

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…

Provides an introduction to latent growth modeling (LGM), a branch of structural equation modeling that facilitates the evaluation of longitudinal change. Fundamental concepts related to growth modeling and notation are introduced; and variations, extensions, and applications of the technique are discussed. Touts LGM's versatility when considering…

Through Monte Carlo simulation, small sample methods for evaluating overall data-model fit in structural equation modeling were explored. Type I error behavior and power were examined using maximum likelihood (ML), Satorra-Bentler scaled and adjusted (SB; Satorra & Bentler, 1988, 1994), residual-based (Browne, 1984), and asymptotically…

In the common two-step structural equation modeling process, modifications are routinely made to the measurement portion of the model prior to assessing structural relations. The effect of such measurement model modifications on the structural parameter estimates, however, is not well known and is the subject of the current investigation. For a…

Secure parental attachment and healthy levels of separation-individuation have been consistently linked to greater college student adjustment. The present study proposes that the relation between parental attachment and college adjustment is mediated by healthy separation-individuation. The authors gathered data on maternal and paternal…