Deborah L Bandalos

The Relative Performance of Full Information Maximum Likelihood Estimation for Missing Data in Structural Equation Models.

A Monte Carlo simulation examined the performance of 4 missing data methods in structural equation models: full information maximum likelihood (FIML), listwise deletion, pairwise deletion, and similar response pattern imputation. The effects of 3 independent variables were examined (factor loading magnitude, sample size, and missing data rate) on 4 outcome measures: convergence failures, parameter estimate bias, parameter estimate efficiency, and model goodness of fit. Results indicated that FIML estimation was superior across all conditions of the design. Under ignorable missing data conditions (missing completely at random and missing at random), FIML estimates were unbiased and more efficient than the other methods. In addition, FIML yielded the lowest proportion of convergence failures and provided near-optimal Type 1 error rates across both simulations.

A Report on the 40-Year Follow-Up of the Torrance Tests of Creative Thinking: Alive and Well in the New Millennium

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 follow-up on the TTCT resulting in a structural equation model, which demonstrates the validity of the TTCT for predicting creative achievement 40 years after its administration. Finally, we provide a rationale for the relevance of the test in schools today.

The Latent Structure and Measurement Invariance of Scores on the Torrance Tests of Creative Thinking-Figural.

There is disagreement among researchers as to whether creativity is a unidimensional or multidimensional trait. Much of the debate centers around the most widely used measure of creativity, the Torrance Tests of Creative Thinking (TTCT). This study used data from 1,000 kindergartners (ages 5-7), 1,000 third graders (ages 7-11) and 1,000 sixth graders (ages 10-13). Confirmatory factor analyses were conducted for both the two-factor model and one-factor model to determine which fit the data better. Measurement invariance across genders and grade levels was assessed using multiple group analyses in which sets of parameters were freed sequentially in a series of hierarchically nested models. The findings indicate that the structure of TTCT scores is consistent with a two-factor theory. Also, the results of the multiple group analyses indicate that model parameters for gender groups are more invariant than for grade levels in determining the fit of the model.

Is Parceling Really Necessary? A Comparison of Results From Item Parceling and Categorical Variable Methodology

This study examined the efficacy of 4 different parceling methods for modeling categorical data with 2, 3, and 4 categories and with normal, moderately nonnormal, and severely nonnormal distributions. The parceling methods investigated were isolated parceling in which items were parceled with other items sharing the same source of variance, and distributed parceling in which items were parceled with items influenced by different factors. These parceling strategies were crossed with strategies in which items were either parceled with similarly distributed or differently distributed items, to create 4 different parceling methods. Overall, parceling together items influenced by different factors and with different distributions resulted in better model fit, but high levels of parameter estimate bias. Across all parceling methods, parameter estimate bias ranged from 20% to over 130%. Parceling strategies were contrasted with use of the WLSMV estimator for categorical, unparceled data. Results based on this estimator are encouraging, although some bias was found when high levels of nonnormality were present. Values of the chi-square and root mean squared error of approximation based on WLSMV also resulted in Type II error rates for misspecified models when data were severely nonnormally distributed.

Accuracy of the Parallel Analysis Procedure With Polychoric Correlations

The purpose of this study was to investigate the application of the parallel analysis (PA) method for choosing the number of factors in component analysis for situations in which data are dichotomous or ordinal. Although polychoric correlations are sometimes used as input for component analyses, the random data matrices generated for use in PA typically consist of Pearson correlations. In this study, the authors matched the type of random data matrix to the type of input matrix. Analyses were conducted on both polychoric and Pearson correlation matrices, and random matrices of the same type (polychoric or Pearson) were generated for the PA procedure. PA based on random Pearson correlations was found to perform at least as well as PA based on random polychoric correlations, for nearly all of the conditions studied.

Theoretical and Statistical Derivation of a Screener for the Behavioral Assessment of Executive Functions in Children

The problem of valid measurement of psychological constructs remains an impediment to scientific progress, and the measurement of executive functions is not an exception. This study examined the statistical and theoretical derivation of a behavioral screener for the estimation of executive functions in children from the well-established Behavior Assessment System for Children (BASC). The original national standardization sample of the BASC-Teacher Rating Scales for children ages 6 through 11 was used (N = 2,165). Moderate-to-high internal consistency was obtained within each factor (.80-.89). A panel of experts was used for content validity examination. A confirmatory factor analysis model with 25 items loading on 4 latent factors (behavioral control, emotional control, attentional control, and problem solving) was developed, and its statistical properties were examined. The multidimensional model demonstrated adequate fit, and it was deemed invariant after configural, metric, and scalar measurement invariance tests across sex and age. Given its strong psychometric properties, with further tests of item validity, this instrument promises future clinical and research utility for the screening of executive functions in school-age children.

Latent Mean and Covariance Differences With Measurement Equivalence in College Students With Developmental Difficulties Versus the Wechsler Adult Intelligence Scale–III/Wechsler Memory Scale–III Normative Sample

Intelligence tests are usually part of the assessment battery for the diagnosis of adults with learning disabilities (LD) and attention deficit hyperactivity disorder (ADHD). Professionals must ensure that inferences drawn from such test scores are equivalent across populations with and without disabilities. Examination of measurement equivalence provides a direct test of the hypothesis that the same set of latent variables underlies a set of test scores in different groups and metric relationships between observed scores and the corresponding latent variables are the same. The hypothesis of measurement equivalence was examined in two samples of college students: one sample with LD and one sample with ADHD. Scores on the third editions of the Wechsler Adult Intelligence and Memory Scales were compared with an age-matched subset of the conorming sample. Results supported the assumption of measurement equivalence but revealed marked differences across samples in latent variable variances and covariances and latent variable means.

The Validity of a Battery of Phonemic and Orthographic Awareness Tasks for Adults With and Without Dyslexia and Attention Deficit/Hyperactivity Disorder:

The vast majority of adults with learning disabilities are those with deficits affecting reading decoding, reading and writing fluency, and spelling. Many adults with Attention Deficit/Hyperactivity Disorder (AD/HD) also demonstrate problems with reading and writing. Documenting the underlying reasons for reading underachievement among these groups of adults is critical from both an assessment and an accommodation perspective. The purposes of this study are threefold: (a) to extend our understanding of the nature of phonemic and orthographic awareness among various adult populations; (b) to explore the validity and separability of the latent constructs of phonemic and orthographic awareness and tasks used to measure these constructs across a population of 630 university students with dyslexia, AD/HD, dyslexia and AD/HD (comorbid), and no disabilities; and (c) to discuss the implications of these analyses for intervention and accommodation selection.