Measurement invariance across time and reporter is rarely reported in the literature for measures of youth disclosure, even though it is often necessary to establish at least strong invariance before proceeding to further analyses such as comparing means across time or reporter. Measurement invariance was examined across time (ages 11, 14, and 17) and across reporter (youth report of disclosure to mother, youth report of disclosure to father, mother report of youth disclosure, father report of youth disclosure) with a sample of 348 youth and their parents. Youth report of disclosure to mothers demonstrated strong invariance across ages 11-14 and 14-17, but strong equivalence was not found for mother report over time across any age. Youth report of disclosure to mothers and fathers demonstrated strong equivalence at ages 11, 14, 17, and across ages 11-14-17. Mother and father reports also demonstrated strong equivalence at ages 11, 14, and 17. The item "I talk with my parent about how I am doing with school work" had lower factor loadings and higher intercepts at age 11 than at other ages for fathers and mothers and compared to youth report. Implications for youth disclosure theory and construct development are discussed.

Factor mixture modeling (FMM) has been increasingly used to investigate unobserved population heterogeneity. This Monte Carlo simulation study examined the issue of measurement invariance testing with FMM when there are covariate effects. Specifically, this study investigated the impact of excluding and misspecifying covariate effects on the class enumeration and measurement invariance testing with FMM. Data were generated based on three FMM models where the covariate had impact on the latent class membership only (population model 1), both the latent class membership and the factor (population model 2), and the latent class membership, the factor, and one item (population model 3). The number of latent classes was fixed at two. These two latent classes were distinguished by factor mean difference for conditions where measurement invariance held in the population, and by both factor mean difference and intercept differences across classes when measurement invariance did not hold in the population. For each of the population models, different analysis models that excluded or misspecified covariate effects were fitted to data. Analyses consisted of two parts. First, for each analysis model, class enumeration rates were examined by comparing the fit of seven solutions: 1-class, 2-class configural, metric, and scalar, and 3-class configural, metric, and scalar. Second, assuming the correct solution was selected, the fit of analysis models with the same solution was compared to identify a best-fitting model. Results showed that completely excluding the covariate from the model (i.e., the unconditional model) would lead to under-extraction of latent classes, except when the class separation was large. Therefore, it is recommended to include covariate in FMM when the focus is to identify the number of latent classes and the level of invariance. Specifically, the covariate effect on the latent class membership can be included if there is no priori hypothesis regarding whether measurement invariance might hold or not. Then fit of this model can be compared with other models that included covariate effects in different ways but with the same number of latent classes and the same level of invariance to identify a best-fitting model.

Researchers have raised concerns about measurement equivalence in comparing personalities across cultures using personality assessments. The self-reported personality measurements often do not assess the same construct, trigger different response styles (i.e., extreme response style), or use behavioral exemplars that are inappropriate across cultures (Byrne&Watkins, 2003; Chen, 2008; Poortinga, van de Vijber,&van Hermert, 2002, van de Vijver&Leung, 1997). James et al. (2005) developed a new measurement system for aggression that is different from traditional personality assessment. It is referred to as the Conditional Reasoning Test for Aggression (CRT-A). The CRT-A is an indirect measure for assessing unconscious motives to be aggressive that was developed in the USA. It has not been studied with people from different cultures. Study 1 investigated the equivalences of the Aggression Questionnaire (AQ) and the CRT-A by administering both to groups of Americans (n=432) and Koreans (n=363). Results based on the exploratory and confirmatory factor analyses and DIF analyses showed that the AQ and CRT-A are not invariant across these cultures. Study 2 replicated LeBreton et al.(2007) study regarding faking issues of the CRT-A with the Korean population. Study 2 found that on the CRT-A, Koreans were able to identify aggressive alternatives when they were told to do so, and Korean students and employees did not score differently on the CRT-A. Implications and future directions of the study are discussed herein.

Children with mild disabilities are known to have difficulties with developing mathematical skills (Hoard, Geary, & Hamson, 1999). Yet, children with mild intellectual disabilities (MIDs) have rarely been included in rigorous scientific research. The present study has three goals. The first goal was to determine the structure of mathematics achievement in elementary aged children with MIDs and children with reading disabilities (RDs) without accompanying mathematics disabilities. The second goal was to establish the measurement stability of mathematics achievement. The third goal was to evaluate students’ response to a mathematics intervention. The participants were 265 children with MIDs and 137 children with RDs. Confirmatory factor analysis and measurement invariance evaluation was utilized to determine the structure of mathematics achievement and to ensure reliable and valid measurement of mathematics achievement between groups across three time points. The results of measurement invariance evaluation indicated that a joint model specification, characterized by two groups, both of which included children with MIDs and children with RDs who were differentiated according to intervention condition participation (not disability status), provided the best account of the underlying data structure. Further, the structure of mathematics achievement in the present sample was unidimensional, and the measurement of mathematics achievement was temporally stable between groups. Finally, latent mathematics achievement growth was evaluated. The results indicated that students in the mathematics intervention condition evidenced an advantage over those in a reading intervention condition at mid- and post-intervention evaluation, while also evidencing more growth in this conceptual domain. Instructional implications are discussed in terms of topic choice and pacing.

Caregivers of persons with dementia, who are often older adults, report sleep disturbance, high rates of depressive symptoms and may be at risk for impaired cognition. This dissertation examined sleep, depressive symptoms, and cognition in older adults and caregivers of persons with dementia. The aims of the review of literature were to understand, in community dwelling adults 60 years and older, the relationships among sleep parameters (sleep onset latency, wake after sleep onset, sleep efficiency, total sleep time, and general sleep complaints), and the domains of cognition (Executive Function, Attention, Episodic Memory, Working Memory, Processing Speed), and global cognition. Based on the findings, the research on the association of subjective sleep parameters and cognition is inconclusive and there is insufficient evidence to confirm or deny the existence of a relationship between objective sleep parameters and cognition. The methods section examined whether in adults 60 years and older, Radloff’s postulated 4-factor structure replicates across Afro-Caribbean Americans, African-Americans, Hispanic-Americans, and European-Americans and determine whether there is evidence for measurement invariance across the four ethnic groups in their responses to the Center for Epidemiological Depression Scale (CES-D) statements. Radloff’s postulated 4-factor model fit the data adequately and the results suggest that there is evidence for configural and partial metric invariance. The final section examined the relationships among subjective sleep parameters (Sleep Onset Latency, Wake After Sleep Onset, Total Sleep Time, Time in Bed, Sleep Efficiency, Sleep Quality), depressive symptoms, and, crystallized, fluid and total cognition in caregivers of persons with dementia with poor sleep. Based on the findings, depressive symptoms also did not mediate the ability of the sleep parameters to predict cognitive performance. With the knowledge that there are potential associations among sleep parameters, depressive symptoms and cognition in caregivers, healthcare providers should collect baseline assessments on sleep, depressive symptoms and cognition from caregivers and monitor them on an ongoing basis to identify changes and intervene in a timely manner. More research studies incorporating measures to capture sleep variability and similar cognitive measures, are needed to clarify the relationships both in older adults and caregivers of persons with dementia.

Intelligence testing has had a relatively long and controversial history, beginning with what is generally considered the first formal measure of intelligence, the Binet-Simon Scales (1916). Questions regarding possible cultural bias in these measures arose virtually simultaneously (e.g. Burt, 1921; Stern, 1914). Over the course of the twentieth and early twenty-first centuries, an abundance of intelligence measures have been developed, with many of them having several revisions, but the issue of test bias remains an important one, both in the professional literature and in the popular press (Reynolds & Lowe, 2009). A current intelligence measure in use, the Differential Ability Scales, Second Edition (DAS-II, Elliott, 2007), is a test with growing popularity for assessment of children and youth, not only for its ease of use, but also for its appeal to young children and its nonverbal composite (among other things). Consequently, it is essential that there be empirical evidence supporting the use of the DAS-II as an appropriate measure of cognitive abilities for children of varying backgrounds. The test publishers conducted extensive research with a representative sample during test development in an effort to ensure that the measure met adequate reliability and validity criteria; however, the issue of test bias, particularly regarding cultural or racial/ethnic groups, was not explicitly addressed. This issue was raised and examined with the original DAS by Keith, Quirk, Schartzer, and Elliott (1999), but with the significant changes made from the first edition to the second, there is no guaranty that the evidence from the earlier would necessarily apply to the latter. The current study investigated whether the DAS-II demonstrates systematic construct bias toward children and youth of any of four ethnic groups: Black, Hispanic, Asian, and White. Multi-group confirmatory factor analysis using data from the DAS-II standardization sample was used to assess whether criteria for increasingly strict levels of invariance were met across groups. Outcomes of this research contribute to an existing body of literature on test bias, as well as provide evidence regarding cross-group construct validity in the DAS-II. Ultimately the results of this study can be used to evaluate the appropriateness of the DAS-II for clinical use with certain ethnic groups and will help to emphasize further the importance of exploring these issues with all standardized tests. / text

Measurement invariance (MI) is a prerequisite to conduct valid comparisons of Health-related quality of life (HRQOL) measures across distinct populations. This research investigated the performance of estimation methods for testing MI hypotheses in complex survey data using a simulation study, and demonstrates the application of these methods for a HRQOL measure. Four forms of MI were tested using confirmatory factory analysis. The simulation study showed that the maximum likelihood method for small sample size and low intraclass correlation (ICC) performed best, whereas the pseudomaximum likelihood with weights and clustering effects performed better for large sample sizes with high ICC to test configural invariance. Both methods performed similarly to test other forms of MI. In the numeric example, MI of one HRQOL measure in the Canadian Community Health Survey was investigated and established for Aboriginal and non-Aboriginal populations with chronic conditions, indicating that they had similar conceptualizations of quality of life.

Measurement invariance (MI) is a prerequisite to conduct valid comparisons of Health-related quality of life (HRQOL) measures across distinct populations. This research investigated the performance of estimation methods for testing MI hypotheses in complex survey data using a simulation study, and demonstrates the application of these methods for a HRQOL measure. Four forms of MI were tested using confirmatory factory analysis. The simulation study showed that the maximum likelihood method for small sample size and low intraclass correlation (ICC) performed best, whereas the pseudomaximum likelihood with weights and clustering effects performed better for large sample sizes with high ICC to test configural invariance. Both methods performed similarly to test other forms of MI. In the numeric example, MI of one HRQOL measure in the Canadian Community Health Survey was investigated and established for Aboriginal and non-Aboriginal populations with chronic conditions, indicating that they had similar conceptualizations of quality of life.

abstract: Standardized intelligence tests are some of the most widely used tests by psychologists. Of these, clinicians most frequently use the Wechsler scales of intelligence. The most recent version of this test for children is the Wechsler Intelligence Scale for Children - Fourth Edition (WISC-IV); given the multiple test revisions that have occurred with the WISC, it is essential to address evidence regarding the structural validity of the test; specifically, that the internal structure of the test corresponds with the structure of the theoretical construct being measured. The current study is the first to investigate the factor structure of the WISC-IV across time for the same individuals. Factorial invariance of the WISC-IV was investigated using a group of 352 students eligible for psychoeducational evaluations tested, on average, 2.8 years apart. One research question was addressed: Does the structure of the WISC-IV remain invariant for the same individuals across time? Using structural equation modeling methods for a four-factor oblique model of the WISC-IV, this study found invariance at the configural and weak levels and partial invariance at the strong and strict levels. This indicated that the overall factor structure remained the same at test and retest with equal precision of the factor loadings at both time points. Three subtest intercepts (BD, CD, and SI) were not equivalent across test and retest; additionally, four subtest error variances (BD, CD, SI, and SS) were not equivalent across test and retest. These results indicate that the WISC-IV measures the same constructs equally well across time, and differences in an individual's cognitive profile can be safely interpreted as reflecting change in the underlying construct across time rather than variations in the test itself. This allows clinicians to be more confident in interpretation of changes in the overall cognitive profile of individual's across time. However, this study's results did not indicate that an individual's test scores should be compared across time. Overall, it was concluded that there is partial measurement invariance of the WISC-IV across time, with invariance of all factor loadings, invariance of all but three intercepts, and invariance of all but four item error variances. / Dissertation/Thesis / Ph.D. Educational Psychology 2012

abstract: Measurement invariance exists when a scale functions equivalently across people and is therefore essential for making meaningful group comparisons. Often, measurement invariance is examined with independent and identically distributed data; however, there are times when the participants are clustered within units, creating dependency in the data. Researchers have taken different approaches to address this dependency when studying measurement invariance (e.g., Kim, Kwok, & Yoon, 2012; Ryu, 2014; Kim, Yoon, Wen, Luo, & Kwok, 2015), but there are no comparisons of the various approaches. The purpose of this master's thesis was to investigate measurement invariance in multilevel data when the grouping variable was a level-1 variable using five different approaches. Publicly available data from the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K) was used as an illustrative example. The construct of early behavior, which was made up of four teacher-rated behavior scales, was evaluated for measurement invariance in relation to gender. In the specific case of this illustrative example, the statistical conclusions of the five approaches were in agreement (i.e., the loading of the externalizing item and the intercept of the approaches to learning item were not invariant). Simulation work should be done to investigate in which situations the conclusions of these approaches diverge. / Dissertation/Thesis / Masters Thesis Psychology 2016