This article updates information about the Torrance Tests of Creative Thinking (TTCT) by reporting on predictive validity data from the most recent data collection point in Torrance's longitudinal studies. First, we outline the background of the tests and changes in scoring over the years. Then, we detail the results of the analyses of the 40-year…

Utilizing longitudinal, 3-wave data collected from multiple informants (fathers, mothers, and target children) in 374 families, the potential effects of sibling relationships on adolescent development across early and middle adolescence were investigated. Adolescents who perceived their sibling relationships more positively at Time 1 tended to…

To synthesize studies that use structural equation modeling (SEM), researchers usually use Pearson correlations (univariate r), Fisher z scores (univariate z), or generalized least squares (GLS) to combine the correlation matrices. The pooled correlation matrix is then analyzed by the use of SEM. Questionable inferences may occur for these ad hoc…

This prospective study examined the effects of maternal characteristics, social support, and risk factors on infant-mother attachment in a heterogeneous sample. Two hundred and six women between the ages of 18 and 40 were interviewed during their last trimester of pregnancy and 1 year postpartum. Structural equation modeling revealed that maternal…

Structural equation modeling (SEM) is a data-analytic technique that allows researchers to test complex theoretical models. Most published applications of SEM involve analyses of cross-sectional recursive (i.e., unidirectional) models, but it is possible for researchers to test more complex designs that involve variables observed at multiple…

Confirmatory factor analytic (CFA) procedures can be used to provide evidence of measurement invariance. However, empirical evaluation has not focused on the accuracy of common CFA steps used to detect a lack of invariance across groups. This investigation examined procedures for detection of test structure differences across groups under several…

The present study used structural equation modeling to examine the potential mediating effect of family conflict on caregiver strain in a randomly drawn household sample of 650 adults with primary care responsibility for an adult age 50 or older with a mental disability. Caregiver strain was directly influenced by the conflict, disagreements, and…

The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for…

This study is a partial replication of L. Hu and P. M. Bentler's (1999) fit criteria work. The purpose of this study was twofold: (a) to determine whether cut-off values vary according to which model is the true population model for a dataset and (b) to identify which of 13 fit indexes behave optimally by retaining all of the correct models while…

Three structural equation models of communication between family members and medical staff were examined to understand relations among staff accessibility, inhibitory family attitudes, getting communication needs met, perceived stress, and satisfaction with communication. Compared to full and direct models, a mediational model fit best in which…

This study investigated the relationship between examinee proficiency and the structure of the Test of English as a Foreign Language (TOEFL) and the Speaking Proficiency in English Assessment Kit (SPEAK). Specifically, using multi-group structural equation modeling, this study tested two competing hypotheses about the relationship: whether or not…

The Penn State Worry Questionnaire (PSWQ) was originally designed as a unifactorial measure of pathological trait worry. However, recent studies supported a two-factor solution with positively worded items loading on the first factor and reverse-scored items loading on a second factor. The current study compared this two-factor model to a negative…

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…

The main objective of this article is to investigate the empirical performances of the Bayesian approach in analyzing structural equation models with small sample sizes. The traditional maximum likelihood (ML) is also included for comparison. In the context of a confirmatory factor analysis model and a structural equation model, simulation studies…

Within the general framework of a multifactor term structure model, the fundamental partial differential equation (PDE) satisfied by a default-free zero-coupon bond price is derived via a martingale-oriented approach. Using this PDE, a result characterizing a model belonging to an exponential affine class is established using only a system of…