Seeing the Forest and the Trees: Comparison of Two IRTree Models to Investigate the Impact of Full Versus Endpoint-Only Response Option Labeling

In this study, we examined the results and interpretations produced from two different IRTree models-one using paths consisting of only dichotomous decisions, and one using paths consisting of both dichotomous and polytomous decisions. We used data from two versions of an impulsivity measure. In the first version, all the response options had labels; in the second version, only the endpoints were labeled. Based on past research, we hypothesized that the endpoints would be selected more frequently in the endpoint-only labeled condition, and the midpoint response option would be selected more frequently in the fully labeled condition. Results from the two models (dichotomous and polytomous) were similar and indicated that our hypotheses were partially supported-specifically, there was no consistent pattern in terms of which condition saw a higher frequency of midpoint response selection. However, our hypotheses regarding extreme responding in the endpoint-only labeling condition were supported.

Does the Spiritual Values/Religion Subscale of the Self-Description Questionnaire III Function Differentially Across Heterosexual and Non-Heterosexual Young Adults? A Measurement Invariance Study

We evaluated the dimensionality and measurement invariance of the Spiritual Values/Religion (SVR) subscale from the Self-Description Questionnaire III across heterosexual and non-heterosexual young adults. We found a one-factor model provided adequate fit to the data for each group, with the SVR items exhibiting configural, metric, and scalar invariance across the two groups. Given that we established measurement invariance, we examined the latent mean difference on the construct and found the heterosexual group reported significantly higher levels of spiritual value/religion than the non-heterosexual group. Our results provided empirical support for the theorized factor structure of the SVR items and the use of the SVR subscale across heterosexual and non-heterosexual young adults, making the scale a viable option for researchers studying religiosity in these specific subpopulations.

Factors Influencing Cross-Validation of Confirmatory Factor Analysis Models

This study investigated, by means of a Monte Carlo study, the use of four cross-validation indices with confirmatory factor analysis models. The influence on the cross-validation indices of three design factors: sample size, loading size, and the degree of model misspecification, was studied. Sample size was varied at 200 and 600, and loading size at .4, .6, and .8. Model misspecifications were introduced by setting nonzero factor loadings to equal zero. A modified version of the Akaike Information Criterion (AIC) obtained very accurate estimates of the two-sample index under all sets of conditions. As expected, larger sample sizes and better specified models resulted in better cross-validation results. The presence of larger factor loadings increased the number of times the cross-validation indices yielded optimal values for the correctly specified model.

Second-Order Confirmatory Factor Analysis of the Reactions to Tests Scale with Cross-Validation

The factor structure of the RTT was evaluated by testing a series of confirmatory factor models including a second-order structure. The results indicated that a reduced 20-item RTT scale fit the data better than the 40-item original RTT and that a second-order structure explained the data very well. The models were cross-validated using several strategies. The reduced RTT was found not to cross-validate in terms of overall fit. However, when the parameter estimates were tested across samples, all parameters were found to be invariant except the item residuals. Because the cross-validation results were not conclusive, the need for additional theoretical and empirical research on the cross-validation of covariance models was discussed.