abstract: Identifying modifiable causes of chronic disease is essential to prepare for the needs of an aging population. Cognitive decline is a precursor to the development of Alzheimer's and other dementing diseases, representing some of the most prevalent and least understood sources of morbidity and mortality associated with aging. To contribute to the literature on cognitive aging, this work focuses on the role of vascular and physical health in the development of cognitive trajectories while accounting for the socioeconomic context where health disparities are developed. The Assets and Health Dynamics among the Oldest-Old study provided a nationally-representative sample of non-institutionalized adults age 65 and over in 1998, with biennial follow-up continuing until 2008. Latent growth models with adjustment for non-random missing data were used to assess vascular, physical, and social predictors of cognitive change. A core aim of this project was examining socioeconomic and racial/ethnic variation in vascular predictors of cognitive trajectories. Results indicated that diabetes and heart problems were directly related to an increased rate of memory decline in whites, where these risk factors were only associated with baseline word-recall for blacks when conditioned on gender and household assets. These results support the vascular hypotheses of cognitive aging and attest to the significance of socioeconomic and racial/ethnic variation in vascular influences on cognitive health. The second substantive portion of this dissertation used parallel process latent growth models to examine the co-development of cognitive and functional health. Initial word-recall scores were consistently associated with later functional limitations, but baseline functional limitations were not consistently associated with later word-recall scores. Gender and household income moderated this relationship, and indicators of lifecourse SES were better equipped to explain variation in initial cognitive and functional status than change in these measures over time. Overall, this work suggests that research examining associations between cognitive decline, chronic disease, and disability must account for the social context where individuals and their health develop. Also, these findings advocate that reducing socioeconomic and racial/ethnic disparities in cognitive health among the aging requires interventions early in the lifecourse, as disparities in cognitive trajectories were solidified prior to late old age. / Dissertation/Thesis / Ph.D. Sociology 2011

abstract: In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required in contrast to second order models that include the measurement and the structural relationships among the variables. However, the use of composites assumes that longitudinal measurement invariance holds; that is, it is assumed that that the relationships among the items and the latent variables remain constant over time. Previous studies conducted on latent growth models (LGM) have shown that when longitudinal metric invariance is violated, the parameter estimates are biased and that mistaken conclusions about growth can be made. The purpose of the current study was to examine the impact of non-invariant loadings and non-invariant intercepts on two longitudinal models: the LGM and the autoregressive quasi-simplex model (AR quasi-simplex). A second purpose was to determine if there are conditions in which researchers can reach adequate conclusions about stability and growth even in the presence of violations of invariance. A Monte Carlo simulation study was conducted to achieve the purposes. The method consisted of generating items under a linear curve of factors model (COFM) or under the AR quasi-simplex. Composites of the items were formed at each time point and analyzed with a linear LGM or an AR quasi-simplex model. The results showed that AR quasi-simplex model yielded biased path coefficients only in the conditions with large violations of invariance. The fit of the AR quasi-simplex was not affected by violations of invariance. In general, the growth parameter estimates of the LGM were biased under violations of invariance. Further, in the presence of non-invariant loadings the rejection rates of the hypothesis of linear growth increased as the proportion of non-invariant items and as the magnitude of violations of invariance increased. A discussion of the results and limitations of the study are provided as well as general recommendations. / Dissertation/Thesis / Ph.D. Psychology 2013

As current educational policies continue to emphasize the importance of college readiness and growth, it is essential to understand the degree to which test scores collected throughout middle school and high school can provide information to make valid inferences about students' college readiness. This thesis sought to summarize the college readiness of Iowa students, describe the nature of student growth, and clarify the relationship between student growth and college readiness. Together, the results support the validity argument that scores from a general achievement test can be used for measuring student growth and making on-track interpretations about college readiness. Results of analyses on the use of benchmarks as indicators of college readiness are presented first. The analyses showed that the state's general achievement test was just as accurate as the ACT when the criterion was defined by grades in domain-specific, credit-bearing courses. Next, latent growth models and growth mixture models were used to summarize and evaluate longitudinal changes in student achievement and their relationship with college outcomes. A calibration sample representing potential college-bound students was used to set the growth trajectories. Then a cohort of students representing the full student population was used to provide validity evidence in support of the growth trajectories. It was shown that students in the highest-performing group could be considered college ready. Several applications of the growth models are also presented. The typical performance on a variety of college outcomes for each developmental group was presented for the validation sample. A second application illustrated how individual patterns of growth in Grade 8 could be used to predict future class membership in Grade 11. This thesis was predicated on the notion that understanding and documenting the nature of student growth, the college readiness of Iowa students, and the relationship between the two is an important step in improving the college readiness of Iowa students and meeting the future needs of an aligned K-16 educational system. As this study is among the first to examine the relationship between college readiness and student growth using modern latent variable modeling techniques with actual college outcomes, guidelines for future research are presented.