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- Genre: Doctoral Dissertation
Description
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.
ContributorsOlivera-Aguilar, Margarita (Author) / Millsap, Roger E. (Thesis advisor) / Levy, Roy (Committee member) / MacKinnon, David (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Each year, millions of aging women will experience menopause, a transition from reproductive capability to reproductive senescence. In women, this transition is characterized by depleted ovarian follicles, declines in levels of sex hormones, and a dysregulation of gonadotrophin feedback loops. Consequently, menopause is accompanied by hot flashes, urogenital atrophy, cognitive decline, and other symptoms that reduce quality of life. To ameliorate these negative consequences, estrogen-containing hormone therapy is prescribed. Findings from clinical and pre-clinical research studies suggest that menopausal hormone therapies can benefit memory and associated neural substrates. However, findings are variable, with some studies reporting null or even detrimental cognitive and neurobiological effects of these therapies. Thus, at present, treatment options for optimal cognitive and brain health outcomes in menopausal women are limited. As such, elucidating factors that influence the cognitive and neurobiological effects of menopausal hormone therapy represents an important need relevant to every aging woman. To this end, work in this dissertation has supported the hypothesis that multiple factors, including post-treatment circulating estrogen levels, experimental handling, type of estrogen treatment, and estrogen receptor activity, can impact the realization of cognitive benefits with Premarin hormone therapy. We found that the dose-dependent working memory benefits of subcutaneous Premarin administration were potentially regulated by the ratios of circulating estrogens present following treatment (Chapter 2). When we administered Premarin orally, it impaired memory (Chapter 3). Follow-up studies revealed that this impairment was likely due to the handling associated with treatment administration and the task difficulty of the memory measurement used (Chapters 3 and 4). Further, we demonstrated that the unique cognitive impacts of estrogens that become increased in circulation following Premarin treatments, such as estrone (Chapter 5), and their interactions with the estrogen receptors (Chapter 6), may influence the realization of hormone therapy-induced cognitive benefits. Future directions include assessing the mnemonic effects of: 1) individual biologically relevant estrogens and 2) clinically-used bioidentical hormone therapy combinations of estrogens. Taken together, information gathered from these studies can inform the development of novel hormone therapies in which these parameters are optimized.
ContributorsEngler-Chiurazzi, Elizabeth (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Sanabria, Federico (Committee member) / Olive, Michael F (Committee member) / Hoffman, Steven (Committee member) / Arizona State University (Publisher)
Created2013
Description
There are several visual dimensions of food that can affect food intake, example portion size, color, and variety. This dissertation elucidates the effect of number of pieces of food on preference and amount of food consumed in humans and motivation for food in animals. Chapter 2 Experiment 1 showed that rats preferred and also ran faster for multiple pieces (30, 10 mg pellets) than an equicaloric, single piece of food (300 mg) showing that multiple pieces of food are more rewarding than a single piece. Chapter 2 Experiment 2 showed that rats preferred a 30-pellet food portion clustered together rather than scattered. Preference and motivation for clustered food pieces may be interpreted based on the optimal foraging theory that animals prefer foods that can maximize energy gain and minimize the risk of predation. Chapter 3 Experiment 1 showed that college students preferred and ate less of a multiple-piece than a single-piece portion and also ate less in a test meal following the multiple-piece than single-piece portion. Chapter 3 Experiment 2 replicated the results in Experiment 1 and used a bagel instead of chicken. Chapter 4 showed that college students given a five-piece chicken portion scattered on a plate ate less in a meal and in a subsequent test meal than those given the same portion clustered together. This is consistent with the hypothesis that multiple pieces of food may appear like more food because they take up a larger surface area than a single-piece portion. All together, these studies show that number and surface area occupied by food pieces are important visual cues determining food choice in animals and both food choice and intake in humans.
ContributorsBajaj, Devina (Author) / Phillips, Elizabeth D. (Thesis advisor) / Cohen, Adam (Committee member) / Johnston, Carol (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2013
Description
Cognitive function declines with normal age and disease states, such as Alzheimer's disease (AD). Loss of ovarian hormones at menopause has been shown to exacerbate age-related memory decline and may be related to the increased risk of AD in women versus men. Some studies show that hormone therapy (HT) can have beneficial effects on cognition in normal aging and AD, but increasing evidence suggests that the most commonly used HT formulation is not ideal. Work in this dissertation used the surgically menopausal rat to evaluate the cognitive effects and mechanisms of progestogens proscribed to women. I also translated these questions to the clinic, evaluating whether history of HT use impacts hippocampal and entorhinal cortex volumes assessed via imaging, and cognition, in menopausal women. Further, this dissertation investigates how sex impacts responsiveness to dietary interventions in a mouse model of AD. Results indicate that the most commonly used progestogen component of HT, medroxyprogesterone acetate (MPA), impairs cognition in the middle-aged and aged surgically menopausal rat. Further, MPA is the sole hormone component of the contraceptive Depo Provera, and my research indicates that MPA administered to young-adult rats leads to long lasting cognitive impairments, evident at middle age. Natural progesterone has been gaining increasing popularity as an alternate option to MPA for HT; however, my findings suggest that progesterone also impairs cognition in the middle-aged and aged surgically menopausal rat, and that the mechanism may be through increased GABAergic activation. This dissertation identified two less commonly used progestogens, norethindrone acetate and levonorgestrel, as potential HTs that could improve cognition in the surgically menopausal rat. Parameters guiding divergent effects on cognition were discovered. In women, prior HT use was associated with larger hippocampal and entorhinal cortex volumes, as well as a modest verbal memory enhancement. Finally, in a model of AD, sex impacts responsiveness to a dietary cognitive intervention, with benefits seen in male, but not female, transgenic mice. These findings have clinical implications, especially since women are at higher risk for AD diagnosis. Together, it is my hope that this information adds to the overarching goal of optimizing cognitive aging in women.
ContributorsBraden, Brittany Blair (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Neisewander, Janet L (Committee member) / Conrad, Cheryl D. (Committee member) / Baxter, Leslie C (Committee member) / Arizona State University (Publisher)
Created2012
Description
Postpartum depression (PPD) is a significant public health concern affecting up to half a million U.S. women annually. Mexican-American women experience substantially higher rates of PPD, and represent an underserved population with significant health disparities that put these women and their infants at greater risk for substantial psychological and developmental difficulties. The current study utilized data on perceived stress, depression, maternal parenting behavior, and infant social-emotional and cognitive development from 214 Mexican-American mother-infant dyads. The first analysis approach utilized a latent intercept (LI) model to examine how overall mean levels and within-person deviations of perceived stress, depressive symptoms, and maternal parenting behavior are related across the postpartum period. Results indicated large, positive between- and within-person correlations between perceived stress and depression. Neither perceived stress nor depressive symptoms were found to have significant between- or within-person associations with the parenting variables. The second analysis approach utilized an autoregressive cross-lagged model with tests of mediation to identify underlying mechanisms among perceived stress, postpartum depressive symptoms, and maternal parenting behavior in the prediction of infant social-emotional and cognitive development. Results indicated that increased depressive symptoms at 12- and 18-weeks were associated with subsequent reports of increased perceived stress at 18- and 24-weeks, respectively. Perceived stress at 12-weeks was found to be negatively associated with subsequent non-hostility at 18-weeks, and both sensitivity and non-hostility were found to be associated with infant cognitive development and social-emotional competencies at 12 months of age (52-weeks), but not with social-emotional problems. The results of the mediation analyses showed that non-hostility at 18- and 24-weeks significantly mediated the association between perceived stress at 12-weeks and infant cognitive development and social-emotional competencies at 52-weeks. The findings extend research that sensitive parenting in early childhood is as important to the development of cognitive ability, social behavior, and emotion regulation in ethnic minority cultures as it is in majority culture families; that maternal perceptions of stress may spillover into parenting behavior, resulting in increased hostility and negatively influencing infant cognitive and social-emotional development; and that symptoms of depressed mood may influence the experience of stress.
ContributorsCiciolla, Lucia (Author) / Crnic, Keith A (Thesis advisor) / West, Stephen G. (Thesis advisor) / Luecken, Linda J. (Committee member) / Presson, Clark C. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Missing data are common in psychology research and can lead to bias and reduced power if not properly handled. Multiple imputation is a state-of-the-art missing data method recommended by methodologists. Multiple imputation methods can generally be divided into two broad categories: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution (e.g., multivariate normal). FCS, on the other hand, imputes variables one at a time, drawing missing values from a series of univariate distributions. In the single-level context, these two approaches have been shown to be equivalent with multivariate normal data. However, less is known about the similarities and differences of these two approaches with multilevel data, and the methodological literature provides no insight into the situations under which the approaches would produce identical results. This document examined five multilevel multiple imputation approaches (three JM methods and two FCS methods) that have been proposed in the literature. An analytic section shows that only two of the methods (one JM method and one FCS method) used imputation models equivalent to a two-level joint population model that contained random intercepts and different associations across levels. The other three methods employed imputation models that differed from the population model primarily in their ability to preserve distinct level-1 and level-2 covariances. I verified the analytic work with computer simulations, and the simulation results also showed that imputation models that failed to preserve level-specific covariances produced biased estimates. The studies also highlighted conditions that exacerbated the amount of bias produced (e.g., bias was greater for conditions with small cluster sizes). The analytic work and simulations lead to a number of practical recommendations for researchers.
ContributorsMistler, Stephen (Author) / Enders, Craig K. (Thesis advisor) / Aiken, Leona (Committee member) / Levy, Roy (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
Coarsely grouped counts or frequencies are commonly used in the behavioral sciences. Grouped count and grouped frequency (GCGF) that are used as outcome variables often violate the assumptions of linear regression as well as models designed for categorical outcomes; there is no analytic model that is designed specifically to accommodate GCGF outcomes. The purpose of this dissertation was to compare the statistical performance of four regression models (linear regression, Poisson regression, ordinal logistic regression, and beta regression) that can be used when the outcome is a GCGF variable. A simulation study was used to determine the power, type I error, and confidence interval (CI) coverage rates for these models under different conditions. Mean structure, variance structure, effect size, continuous or binary predictor, and sample size were included in the factorial design. Mean structures reflected either a linear relationship or an exponential relationship between the predictor and the outcome. Variance structures reflected homoscedastic (as in linear regression), heteroscedastic (monotonically increasing) or heteroscedastic (increasing then decreasing) variance. Small to medium, large, and very large effect sizes were examined. Sample sizes were 100, 200, 500, and 1000. Results of the simulation study showed that ordinal logistic regression produced type I error, statistical power, and CI coverage rates that were consistently within acceptable limits. Linear regression produced type I error and statistical power that were within acceptable limits, but CI coverage was too low for several conditions important to the analysis of counts and frequencies. Poisson regression and beta regression displayed inflated type I error, low statistical power, and low CI coverage rates for nearly all conditions. All models produced unbiased estimates of the regression coefficient. Based on the statistical performance of the four models, ordinal logistic regression seems to be the preferred method for analyzing GCGF outcomes. Linear regression also performed well, but CI coverage was too low for conditions with an exponential mean structure and/or heteroscedastic variance. Some aspects of model prediction, such as model fit, were not assessed here; more research is necessary to determine which statistical model best captures the unique properties of GCGF outcomes.
ContributorsCoxe, Stefany (Author) / Aiken, Leona S. (Thesis advisor) / West, Stephen G. (Thesis advisor) / Mackinnon, David P (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Cognitive function is multidimensional and complex, and research indicates that it is impacted by age, lifetime experience, and ovarian hormone milieu. One particular domain of cognitive function that is susceptible to age-related decrements is spatial memory. Cognitive practice can affect spatial memory when aged in both males and females, and in females alone ovarian hormones have been found to alter spatial memory via modulating brain microstructure and function in many of the same brain areas affected by aging. The research in this dissertation has implications that promote an understanding of the effects of cognitive practice on aging memory, why males and females respond differently to cognitive practice, and the parameters and mechanisms underlying estrogen's effects on memory. This body of work suggests that cognitive practice can enhance memory when aged and that estrogen is a probable candidate facilitating the observed differences in the effects of cognitive practice depending on sex. This enhancement in cognitive practice effects via estrogen is supported by data demonstrating that estrogen enhances spatial memory and hippocampal synaptic plasticity. The estrogen-facilitated memory enhancements and alterations in hippocampal synaptic plasticity are at least partially facilitated via enhancements in cholinergic signaling from the basal forebrain. Finally, age, dose, and type of estrogen utilized are important factors to consider when evaluating estrogen's effects on memory and its underlying mechanisms, since age alters the responsiveness to estrogen treatment and the dose of estrogen needed, and small alterations in the molecular structure of estrogen can have a profound impact on estrogen's efficacy on memory. Collectively, this dissertation elucidates many parameters that dictate the outcome, and even the direction, of the effects that cognitive practice and estrogens have on cognition during aging. Indeed, many parameters including the ones described here are important considerations when designing future putative behavioral interventions, behavioral therapies, and hormone therapies. Ideally, the parameters described here will be used to help design the next generation of interventions, therapies, and nootropic agents that will allow individuals to maintain their cognitive capacity when aged, above and beyond what is currently possible, thus enacting lasting improvement in women's health and public health in general.
ContributorsTalboom, Joshua S (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Conrad, Cheryl D. (Committee member) / Neisewander, Janet L (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2011
Description
Understanding how adherence affects outcomes is crucial when developing and assigning interventions. However, interventions are often evaluated by conducting randomized experiments and estimating intent-to-treat effects, which ignore actual treatment received. Dose-response effects can supplement intent-to-treat effects when participants are offered the full dose but many only receive a partial dose due to nonadherence. Using these data, we can estimate the magnitude of the treatment effect at different levels of adherence, which serve as a proxy for different levels of treatment. In this dissertation, I conducted Monte Carlo simulations to evaluate when linear dose-response effects can be accurately and precisely estimated in randomized experiments comparing a no-treatment control condition to a treatment condition with partial adherence. Specifically, I evaluated the performance of confounder adjustment and instrumental variable methods when their assumptions were met (Study 1) and when their assumptions were violated (Study 2). In Study 1, the confounder adjustment and instrumental variable methods provided unbiased estimates of the dose-response effect across sample sizes (200, 500, 2,000) and adherence distributions (uniform, right skewed, left skewed). The adherence distribution affected power for the instrumental variable method. In Study 2, the confounder adjustment method provided unbiased or minimally biased estimates of the dose-response effect under no or weak (but not moderate or strong) unobserved confounding. The instrumental variable method provided extremely biased estimates of the dose-response effect under violations of the exclusion restriction (no direct effect of treatment assignment on the outcome), though less severe violations of the exclusion restriction should be investigated.
ContributorsMazza, Gina L (Author) / Grimm, Kevin J. (Thesis advisor) / West, Stephen G. (Thesis advisor) / Mackinnon, David P (Committee member) / Tein, Jenn-Yun (Committee member) / Arizona State University (Publisher)
Created2018
Description
Food is an essential driver of animal behavior. For social organisms, the acquisition of food guides interactions with the environment and with group-mates. Studies have focused on how social individuals find and choose food sources, and share both food and information with group-mates. However, it is often not clear how experiences throughout an individual's life influence such interactions. The core question of this thesis is how individuals’ experience contributes to within-caste behavioral variation in a social group. I investigate the effects of individual history, including physical injury and food-related experience, on individuals' social food sharing behavior, responses to food-related stimuli, and the associated neural biogenic amine signaling pathways. I use the eusocial honey bee (Apis mellifera) system, one in which individuals exhibit a high degree of plasticity in responses to environmental stimuli and there is a richness of communicatory pathways for food-related information. Foraging exposes honey bees to aversive experiences such as predation, con-specific competition, and environmental toxins. I show that foraging experience changes individuals' response thresholds to sucrose, a main component of adults’ diets, depending on whether foraging conditions are benign or aversive. Bodily injury is demonstrated to reduce individuals' appetitive responses to new, potentially food-predictive odors. Aversive conditions also impact an individual's social food sharing behavior; mouth-to-mouse trophallaxis with particular groupmates is modulated by aversive foraging conditions both for foragers who directly experienced these conditions and non-foragers who were influenced via social contact with foragers. Although the mechanisms underlying these behavioral changes have yet to be resolved, my results implicate biogenic amine signaling pathways as a potential component. Serotonin and octopamine concentrations are shown to undergo long-term change due to distinct foraging experiences. My work serves to highlight the malleability of a social individual's food-related behavior, suggesting that environmental conditions shape how individuals respond to food and share information with group-mates. This thesis contributes to a deeper understanding of inter-individual variation in animal behavior.
ContributorsFinkelstein, Abigail (Author) / Amdam, Gro V (Thesis advisor) / Conrad, Cheryl (Committee member) / Smith, Brian (Committee member) / Neisewander, Janet (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2017