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The factorial validity and gender invariance of the Beck Depression Inventory -- Second Edition (BDI-II) and the Multidimensional Pain Inventory (MPI) were examined in large samples of women and men with chronic pain. These measures are commonly employed in the assessment of individuals with chronic pain. Moreover, the BDI and the MPI Interference subscale are recommended by the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT) committee for use in pain research. In Article I, four competing models of the BDI-II factor structure were examined and confirmatory factor analysis supported the conceptualization of depression as a singular latent construct, within a hierarchical factor structure consisting of three first-order factors -- Negative Attitude, Performance Difficulty, and Somatic Elements. Factor structure, item-total correlations, and correlations between subscale means and subjective pain experience, support the inclusion of somatic items despite concerns regarding their overlap with pain symptoms. Given partial measurement gender invariance, an examination of mean gender differences was warranted. The scores of women and men were similar. In Article II, models of the MPI factor structure [Kerns et al., 1985 with admendments by Rudy, 1989 and Deisinger et al., 2001] were examined. The Interference factor was cross-validated except for one problematic item, and is gender invariant. When configured according to the Deisinger Model, the Punishing Responses and Pain Severity factors provide valid, gender equivalent, information. The Support, Solicitous and Distracting Responses factors operated differently by gender. Although neither model is optimal for Section III, the Kerns Model is best. The Activities Away From Home and Social Activities factors are gender invariant, but Outdoor Work and Household Chores are not. Revisions to Sections II and III are recommended. With its focus on construct validity and gender equivalence, this dissertation complements recent calls for empirically supported measurement and is consistent with gender-fair research initiatives. Results impact chronic pain clinicians and researchers.

Theoretical and empirical relationships between paired comparison, PC, same-different choice times and perceived difficulty on a cartwheel task are investigated. An ordering of pairs of stimuli by the use of discrimination choice time predicts the subject's ordering of these pairs according to difficulty of discrimination. Two general models are developed to predict unilateral similarity proportions from PC response latencies. Though both models predict that unilateral similarity proportions are related to directional PC choices, only the ratio of differences model predicts the obtained standard stimulus effect. / Arts, Faculty of / Psychology, Department of / Graduate

Coefficient Omega was introduced by McDonald (1978) as a reliability coefficient of composite scores for the congeneric model. Interval estimation (Neyman, 1937) on coefficient Omega provides a range of plausible values which is likely to capture the population reliability of composite scores. The Wald method, likelihood method, and bias-corrected and accelerated bootstrap method are three methods to construct confidence interval for coefficient Omega (e.g., Cheung, 2009b; Kelley & Cheng, 2012; Raykov, 2002, 2004, 2009; Raykov & Marcoulides, 2004; Padilla & Divers, 2013). Very limited number of studies on the evaluation of these three methods can be found in the literature (e.g., Cheung, 2007, 2009a, 2009b; Kelley & Cheng, 2012; Padilla & Divers, 2013). No simulation study has been conducted to evaluate the performance of these three methods for interval construction on coefficient Omega. In the current simulation study, I assessed these three methods by comparing their empirical performance on interval estimation for coefficient Omega. Four factors were included in the simulation design: sample size, number of items, factor loading, and degree of nonnormality. Two thousands datasets were generated in R 2.15.0 (R Core Team, 2012) for each condition. For each generated dataset, three approaches (i.e., the Wald method, likelihood method, and bias-corrected and accelerated bootstrap method) were used to construct 95% confidence interval of coefficient Omega in R 2.15.0. The results showed that when the data were multivariate normally distributed, three methods performed equally well and coverage probabilities were very close to the prespecified .95 confidence level. When the data were multivariate nonnormally distributed, coverage probabilities decreased and interval widths became wider for all three methods as the degree of nonnormality increased. In general, when the data departed from the multivariate normality, the BCa bootstrap method performed better than the other two methods, with relatively higher coverage probabilities, while the Wald and likelihood methods were comparable and yielded narrower interval width than the BCa bootstrap method. / A Thesis submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Master of Science. / Fall Semester, 2014. / August 11, 2014. / coefficient omega, confidence interval, reliability, structural equation modeling / Includes bibliographical references. / Yanyun Yang, Professor Directing Thesis; Betsy Becker, Committee Member; Russell Almond, Committee Member.