Multiple-indicators multiple-causes (MIMIC) modeling is often employed for measurement invariance testing under the structural equation modeling framework. This Monte Carlo study explored the behaviors of MIMIC as a measurement invariance testing method in different research situations. First, the performance of MIMIC under the factor loading noninvariance conditions was investigated through model fit evaluations and likelihood ratio tests. This study demonstrated that the violation of factor loading invariance was not detected by any of the typically reported model fit indices. Consistently, the likelihood ratio tests for MIMIC models exhibited poor performance in identifying noninvariance in factor loadings. That is, MIMIC was insensitive to the presence of factor loading noninvariance, which implies that factor loading invariance should be examined through other measurement invariance testing techniques. To control Type I error inflation in detecting the noninvariance of intercepts or thresholds, this simulation study with both continuous and categorical variables employed the likelihood ratio test with two critical value adjustment strategies, Oort adjustment and Bonferroni correction. The simulation results showed that the likelihood ratio test with Oort adjustment not only controlled Type I error rates below the basal Type I error rates but also maintained high power across study conditions. However, it was observed that power to detect the noninvariant variables slightly attenuated with multiple (i.e., two) noninvariant variables in a model. Given that the modification index is the chi-square difference after relaxing one parameter for estimation, this study investigated modification indices under four research scenarios based on a combination of the cutoffs of modification indices and the procedures of model modification: (a) the noniterative method (i.e., modification indices at the initial stage of model modification) using the conventional critical value, (b) the noniterative method using the Oort adjusted critical value, (c) the iterative procedure of model modification using the conventional critical value, and (d) the iterative procedure using the Oort adjustment. The iterative model search procedure using modification indices showed high performance in detecting noninvariant variables even without critical value adjustment, which indicates that iterative model search specification does not require critical value adjustment in identifying the noninvariance correctly. On the other hand, when the noniterative procedure was used, the Oort adjustment yielded adequate results.

The present study examined the factor structure of the Penn State Worry Questionnaire (PSWQ), the Student Worry Questionnaire-30 (SWQ-30), the Anxious Thoughts Inventory (AnTI), the Ruminative Responses Scale (RRS), and the Rumination-Reflection Questionnaire (RRQ). The present study also examined the measurement invariance between men (n = 186) and women (n = 316) in a university sample. Different models for each measure were identified through a review of the literature, and the models were examined through confirmatory factor analyses. The best-fitting models for each measure were retained for subsequent model modification to improve fit and for invariance testing across gender. The results of the confirmatory factor analyses and subsequent exploratory models provided general support for invariance in the configural models, but only the RRQ displayed measurement, scalar, and latent mean structure invariance. Results of the bootstrapped regression analyses indicated that summated scores derived from the exploratory models demonstrated different relationships between anxiety and depression in men and women. Frequency of worry, metaworry, and general anxiety symptoms significantly contributed to prediction of anxiety in men, whereas metaworry, social worry, lethargy, general anxiety symptoms, and health worries predicted anxiety in women. Social worry, metaworry, recrimination, and reflection (negatively) contributed to prediction of depression in men, whereas social worry, metaworry, lethargy, general anxiety symptoms, and social adequacy concerns predicted depression in women.

College student and Amazon's Mechanical TURK (MTURK) samples are regularly utilized in trauma research. Recent literature, however, has criticized these samples for not being generalizable to the general U.S. population. Measurement invariance (MI) using confirmatory factor analyses (CFA), is rarely utilized in trauma research, even though the analysis can determine whether groups are invariant across factor structure, factor loadings, item intercepts, and residual error variances on a given measure of PTSD symptom severity. The purpose of this study was to determine whether college student (n = 255) and MTURK (n = 316) samples are invariant on the PCL-5. Model fit indices indicated the 7-factor Hybrid model was the best fitting model, but the 6-factor anhedonia model was the most parsimonious model. Both models demonstrated equivalence in factor structures (configural invariance), factor loadings (metric invariance), intercepts (scalar invariance), and residuals (strict invariance), indicating MTURK and college student samples are similar in regards to PTSD symptom severity. These findings provide evidence that these groups can be combined in future studies to increase sample size for trauma research. Only the Anhedonia factor exhibited mean differences between groups, which may be related to true differences between college students and MTURK survey-takers. Thus, there is further evidence that the findings from trauma studies using these populations are generalizable to each other.

The objective of this dissertation was to examine the relation between shyness and quality of life (QoL) among adults with schizophrenia in a series of three studies. I first began by understanding whether commonly used measures of shyness and sociability were reliable in this population (Study 1). Next, I examined two moderating variables related to stress-responses subserved by the central (Study 2) and peripheral (Study 3) nervous systems. Study 1, used self-report questionnaires of shyness and sociability to determine whether individuals with schizophrenia responded to these questionnaires in the same way as healthy controls. Studies 2 and 3 used linear regression analyses to determine whether passive neural responses (ERP’s) to social stimuli (emotional faces) and hormonal levels (baseline salivary cortisol and testosterone), respectively, moderated the relation between shyness and QoL. I found that individuals with schizophrenia responded to self-reported shyness and sociability items in a similar way as their nonclinical peers, suggesting that self-reported shyness and sociability are equivalent across populations (Study 1). Study 2, found that individuals who were shy and displayed a hyposensitivity to the processing of fearful faces displayed the lowest QoL. Those who were shy and took longer to process happy faces also demonstrated hindered QoL. Finally, individuals who were shy and had relatively lower baseline salivary cortisol levels also had the lowest QoL. In all circumstances, individuals who were relatively less shy were not susceptible to factors relating to the central and peripheral nervous system. The results of these three studies show that interpretations of findings using self-reported measures of shyness and sociability can be made with confidence in this population. The results also provide support that factors related to processing stressful stimuli can influence the relation between shyness and QoL, thereby further increasing our understanding of this nuanced relation. Theoretical and practical implications of these findings are discussed. / Dissertation / Candidate in Philosophy / Individuals with schizophrenia have been shown to experience reduced quality of life (QoL). Many studies have tried to understand what factors lead to reduced QoL, with one of them being individual differences in personality. This dissertation focused on the personality trait of shyness and addressed two main questions: 1. Are we correctly measuring shyness in people with schizophrenia? 2. What other factors influence the relation between shyness and QoL among individuals with schizophrenia? I first examined whether the meaning of shyness was equivalent between adults with schizophrenia and nonclinical controls. I then examined two different biological factors (i.e., neural and hormonal) related to stress responses to see if they influenced the relation between shyness and QoL in adults with schizophrenia. The answers to these questions have theoretical and practical implications for helping us understand who is at increased and decreased risk for experiencing hindered QoL, and possible targets for intervention.

abstract: To make meaningful comparisons on a construct of interest across groups or over time, measurement invariance needs to exist for at least a subset of the observed variables that define the construct. Often, chi-square difference tests are used to test for measurement invariance. However, these statistics are affected by sample size such that larger sample sizes are associated with a greater prevalence of significant tests. Thus, using other measures of non-invariance to aid in the decision process would be beneficial. For this dissertation project, I proposed four new effect size measures of measurement non-invariance and analyzed a Monte Carlo simulation study to evaluate their properties and behavior in addition to the properties and behavior of an already existing effect size measure of non-invariance. The effect size measures were evaluated based on bias, variability, and consistency. Additionally, the factors that affected the value of the effect size measures were analyzed. All studied effect sizes were consistent, but three were biased under certain conditions. Further work is needed to establish benchmarks for the unbiased effect sizes. / Dissertation/Thesis / Doctoral Dissertation Psychology 2019

Students' retention in STEM-related careers is of great concern for educators and researchers, especially the retention of underrepresented groups such as females, Hispanics, and Blacks in these careers. Therefore it is important to study factors that could potentially influence students' decision to stay in STEM. The work described in this dissertation involved three research studies where assessments have been used in college chemistry courses to assess students' prior content knowledge, chemistry-self-efficacy, and attitude toward science. These three factors have been suggested to have an influence on students' performance in a course and could eventually be a retention factor. The first research study involved the development and use of an instrument to measure biochemistry prior knowledge of foundational concepts from chemistry and biology that are considered important for biochemistry learning. This instrument was developed with a parallel structure where three items were used to measure a concept and common incorrect ideas were used as distractors. The specific structure of this instrument allows the identification of common incorrect ideas that students have when entering biochemistry and that can hinder students' learning of biochemistry concepts. This instrument was given as pre/posttest to students enrolled in introductory biochemistry courses. The findings indicated that some incorrect ideas are persistent even after instruction, as is the case for bond energy and the structure of the alpha helix concepts. This study highlights the importance of measuring prior conceptual knowledge; so that instructors can plan interventions to help students overcome their incorrect ideas. For the second research study, students' chemistry self-efficacy was measured five times during a semester of preparatory college chemistry. Chemistry self-efficacy beliefs have been linked to students' achievement, and students with stronger self-efficacy are more likely to try challenging tasks and persist in them, which will help them to stay in STEM. Using multilevel modeling analysis to examine potential differences in students' self-efficacy beliefs by sex and race/ethnicity, it was found that there were some differences in the trends by race/ethnicity. In particular, we found that for Hispanic and Black males the trends were negative when compared with White males. This study highlights the importance of measuring self-efficacy at different time points in the semester and for instructors to be aware of potential differences in their students' confidence when working on a chemistry task. The third research study involves the use of the Test of Science Related Attitudes (TOSRA) in an introductory chemistry course. A shortened version of the instrument that includes three scales, normality of scientists, attitude toward inquiry, and career interest in science was used. The first purpose of this study was to gather validity evidence for the internal structure of the instrument with college chemistry students. Using measurement invariance analysis by sex and race/ethnicity, it was found that the internal structure holds by sex, but it did not hold for Blacks in our sample. Further analysis revealed problems with the normality scales for Blacks. The second purpose was to examine the relationship between the scales of TOSRA, achievement in chemistry, and math prior knowledge. Using Structural Equation Modeling (SEM) it was found that two of the TOSRA scales, attitude toward inquiry and career interest in science, have a small but significant influence on students' achievement in chemistry. This study highlights the importance of examining if the scores apply similarly for different group of students in a population, since the scores on these assessments could be used to make decisions that will affect student. The research studies presented in this work are a step forward with our intention to understand better the factors that can influence students' decisions to stay or leave STEM-related careers. Each study has provided psychometric evidence for the use of three different assessments in college chemistry courses. Instructors can use these assessments in large and small lecture classrooms. Information obtained from these assessments can then be used to make target interventions to help students learn and/or be more confident on a given task. Also, it highlights the importance to look at different group of students, such as the underrepresented groups, since response trends may be different. Being aware of students' diverse needs will help us to understand some of the challenges that student face in the chemistry classroom. Understanding some of these challenges will help instructors be more prepared for teaching.

The purpose of the present study was to examine the invariance of the factor structure and item response model parameter estimates obtained from a set of 27 items selected from the 2002 and 2003 forms of Your First College Year (YFCY). The first major research question of the present study was: How similar/invariant are the factor structures obtained from two datasets (i.e., identical items, different people)? The first research question was addressed in two parts: (1) Exploring factor structures using the YFCY02 dataset; and (2) Assessing factorial invariance using the YFCY02 and YFCY03 datasets. After using exploratory and confirmatory and factor analysis for ordered data, a four-factor model using 20 items was selected based on acceptable model fit for the YFCY02 and YFCY03 datasets. The four factors (constructs) obtained from the final model were: Overall Satisfaction, Social Agency, Social Self Concept, and Academic Skills. To assess factorial invariance, partial and full factorial invariance were examined. The four-factor model fit both datasets equally well, meeting the criteria for partial and full measurement invariance. The second major research question of the present study was: How similar/invariant are person and item parameter estimates obtained from two different datasets (i.e., identical items, different people) for the homogenous graded response model (Samejima, 1969) and the partial credit model (Masters, 1982)? To evaluate measurement invariance using IRT methods, the item discrimination and item difficulty parameters obtained from the GRM need to be equivalent across datasets. The YFCY02 and YFCY03 GRM item discrimination parameters (slope) correlation was 0.828. The YFCY02 and YFCY03 GRM item difficulty parameters (location) correlation was 0.716. The correlations and scatter plots indicated that the item discrimination parameter estimates were more invariant than the item difficulty parameter estimates across the YFCY02 and YFCY03 datasets.

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<p>Previous research has identified impulsive personality traits as significant risk factors for a wide range of risk-taking behavior, substance use, and clinical problems. Most work has been conducted in primarily White samples, leaving it unclear whether these patterns generalize to racial and ethnic minorities, who have higher rates of negative consequences of substance use behavior. The most widely used assessment of impulsive traits is the UPPS-P Impulsive Behavior scale, which has strong psychometric properties across demographic subgroups, such as gender and age; however, data supporting its use in racial and ethnic minorities is less well-developed. The aims of this study are to 1) examine the measurement invariance of the UPPS-P Impulsive Behavior Scale-Short Form (Cyders et al., 2014) across racial minority groups and 2) determine if impulsive personality traits differentially relate to substance use outcomes across racial groups. Participants were 1301young adults (ages 18-35, fluent in English), recruited through an online survey for both college students at a large public university and Mechanical Turk, a crowdsourcing online platform. Measurement invariance was assessed using multigroup confirmatory factor analysis. Differential validity was assessed using a structural equation modeling framework. I established model fit for each racial group (White group: RMSEA= .067, CFI= .94; Black group: RMSEA= .071, 90% CFI= .952; Asian American group: RMSEA= .073, CFI= .94; Hispanic group: RMSEA=.081, CFI=.934). Based on change in CFI/RMSEA indices, I concluded strong measurement invariance of the Short UPPS-P as a valid scale of impulsive behavior across racial groups. In the White group, findings indicated significant relationships between multiple SUPPS-P traits and alcohol and substance use. In the Asian American group, positive relationships were found between sensation and alcohol use (<i>p</i>=.015) and negative urgency and drug use (<i>p</i>=.020). I found that there were no differences in the relationships between the Short UPPS-P traits and substance use outcomes across White and the racial and ethnic groups studied (<i>p</i>’s>.06). </p>

Indiana University-Purdue University Indianapolis (IUPUI) / Previous research has identified impulsive personality traits as significant risk factors for a wide range of risk-taking behavior, substance use, and clinical problems. Most work has been conducted in primarily White samples, leaving it unclear whether these patterns generalize to racial and ethnic minorities, who have higher rates of negative consequences of substance use behavior. The most widely used assessment of impulsive traits is the UPPS-P Impulsive Behavior scale, which has strong psychometric properties across demographic subgroups, such as gender and age; however, data supporting its use in racial and ethnic minorities is less well-developed. The aims of this study are to 1) examine the measurement invariance of the UPPS-P Impulsive Behavior Scale-Short Form (Cyders et al., 2014) across racial minority groups and 2) determine if impulsive personality traits differentially relate to substance use outcomes across racial groups. Participants were 1301 young adults (ages 18-35, fluent in English), recruited through an online survey for both college students at a large public university and Mechanical Turk, a crowdsourcing online platform. Measurement invariance was assessed using multigroup confirmatory factor analysis. Differential validity was assessed using a structural equation modeling framework. I established model fit for each racial group (White group: RMSEA= .067, CFI= .94; Black group: RMSEA= .071, 90% CFI= .952; Asian American group: RMSEA= .073, CFI= .94; Hispanic group: RMSEA=.081, CFI=.934). Based on change in CFI/RMSEA indices, I concluded strong measurement invariance of the Short UPPS-P as a valid scale of impulsive behavior across racial groups. In the White group, findings indicated significant relationships between multiple SUPPS-P traits and alcohol and substance use. In the Asian American group, positive relationships were found between sensation and alcohol use (p=.015) and negative urgency and drug use (p=.020). I found that there were no differences in the relationships between the Short UPPS-P traits and substance use outcomes across White and the racial and ethnic groups studied (p’s>.06).