The question as to which structural equation model should be selected when multitrait-multimethod (MTMM) data are analyzed is of interest to many researchers. In the past, attempts to find a well-fitting model have often been data-driven and highly arbitrary. In the present article, the authors argue that the measurement design (type of methods…

Many social science theories that examine the connection between beliefs and behaviors assume that belief constructs will predict behaviors similarly across development. Converging research implies that this assumption may not be tenable across all ages or all belief constructs. Thus, to test this implication, the relation between behavior and…

Normal theory maximum likelihood (ML) is by far the most popular estimation and testing method used in structural equation modeling (SEM), and it is the default in most SEM programs. Even though this approach assumes multivariate normality of the data, its use can be justified on the grounds that it is fairly robust to the violations of the…

The International Dyslexia Association defines dyslexia as unexpected problems of neurobiological origin in accuracy and rate of oral reading of single real words, single pseudowords, or text or of written spelling. However, prior research has focused more on the reading than the spelling problems of students with dyslexia. A test battery was…

This study examined the bidirectional development of aggressive response evaluation and decision (RED) and antisocial behavior across five time points in adolescence. Participants (n = 522) were asked to imagine themselves behaving aggressively while viewing videotaped ambiguous provocations and answered a set of RED questions following each…

Data from Mexico City, Mexico (N = 978) and from Texas, USA (N = 932) were used to test the predictive validity of the teacher professional development component of the Will, Skill, Tool Model of Technology Integration in a cross-cultural context. Structural equation modeling (SEM) was used to test the model. Analyses of these data yielded…

The present study used Canadian National Longitudinal data to examine a model of the mechanisms through which the effects of neighborhood socioeconomic conditions impact young children's verbal and behavioral outcomes (N = 3,528; M age = 5.05 years, SD= 0.86). Integrating elements of social disorganization theory and family stress models, and…

D. B. Rubin's model for causal inference in experiments and observational studies is enlarged to analyze the problem of "causes causing causes" and is compared to path analysis and recursive structural equations models. A special quasiexperimental design, the encouragement design, is used to give concreteness to the discussion by…

A Monte Carlo study evaluated the effectiveness of different factor analysis extraction and rotation methods for identifying the known population multiple-indicator measurement model. Results demonstrate that exploratory factor analysis can contribute to a useful heuristic strategy for model specification prior to cross-validation with…

Reviews recent developments in structural equation modeling (SEM). Discusses issues critical to designing and evaluating SEM studies and recent technological developments. Examines innovations in applying SEM to different research contexts and designs. Also discusses procedures for redressing common problems and misunderstandings in the…

Proposes a novel structural modeling approach based on latent growth curve model specifications for use with dyadic data. The approach allows researchers to test more sophisticated causal models, incorporate latent variables, and estimate more complex error structures than is currently possible using hierarchical linear modeling or multilevel…

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)

Introduces an alternative structural equation modeling (SEM) specification search approach based on the Tabu search procedure. Using data with known structure, the procedure is illustrated, and its capabilities for specification searches in SEM are demonstrated. (Author/SLD)

Provides counterexamples where the covariance matrix provides crucial information about consequential model misspecifications and cautions researchers about overinterpreting the conclusion of D. Rogosa and J. Willett (1985) that the covariance matrix is a severe summary of longitudinal data that may discard crucial information about growth. (SLD)

Illustrates how structural equation modeling can be used to test the multidimensionality of a measure. Using data collected on a multidimensional measure, compares an oblique factor model with a higher order factor model, and shows how the oblique factor model fits the data better. (SLD)