Matching Items (20)
Description
The comparison of between- versus within-person relations addresses a central issue in psychological research regarding whether group-level relations among variables generalize to individual group members. Between- and within-person effects may differ in magnitude as well as direction, and contextual multilevel models can accommodate this difference. Contextual multilevel models have been explicated mostly for cross-sectional data, but they can also be applied to longitudinal data where level-1 effects represent within-person relations and level-2 effects represent between-person relations. With longitudinal data, estimating the contextual effect allows direct evaluation of whether between-person and within-person effects differ. Furthermore, these models, unlike single-level models, permit individual differences by allowing within-person slopes to vary across individuals. This study examined the statistical performance of the contextual model with a random slope for longitudinal within-person fluctuation data.
A Monte Carlo simulation was used to generate data based on the contextual multilevel model, where sample size, effect size, and intraclass correlation (ICC) of the predictor variable were varied. The effects of simulation factors on parameter bias, parameter variability, and standard error accuracy were assessed. Parameter estimates were in general unbiased. Power to detect the slope variance and contextual effect was over 80% for most conditions, except some of the smaller sample size conditions. Type I error rates for the contextual effect were also high for some of the smaller sample size conditions. Conclusions and future directions are discussed.
A Monte Carlo simulation was used to generate data based on the contextual multilevel model, where sample size, effect size, and intraclass correlation (ICC) of the predictor variable were varied. The effects of simulation factors on parameter bias, parameter variability, and standard error accuracy were assessed. Parameter estimates were in general unbiased. Power to detect the slope variance and contextual effect was over 80% for most conditions, except some of the smaller sample size conditions. Type I error rates for the contextual effect were also high for some of the smaller sample size conditions. Conclusions and future directions are discussed.
ContributorsWurpts, Ingrid Carlson (Author) / Mackinnon, David P (Thesis advisor) / West, Stephen G. (Committee member) / Grimm, Kevin J. (Committee member) / Suk, Hye Won (Committee member) / Arizona State University (Publisher)
Created2016
Description
This paper investigates a relatively new analysis method for longitudinal data in the framework of functional data analysis. This approach treats longitudinal data as so-called sparse functional data. The first section of the paper introduces functional data and the general ideas of functional data analysis. The second section discusses the analysis of longitudinal data in the context of functional data analysis, while considering the unique characteristics of longitudinal data such, in particular sparseness and missing data. The third section introduces functional mixed-effects models that can handle these unique characteristics of sparseness and missingness. The next section discusses a preliminary simulation study conducted to examine the performance of a functional mixed-effects model under various conditions. An extended simulation study was carried out to evaluate the estimation accuracy of a functional mixed-effects model. Specifically, the accuracy of the estimated trajectories was examined under various conditions including different types of missing data and varying levels of sparseness.
ContributorsWard, Kimberly l (Author) / Suk, Hye Won (Thesis advisor) / Aiken, Leona (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2016
Description
Given the major investment young people make in earning and maintaining a peer reputation, our goal in this study was to explore the association between dimensions of negative and positive peer reputation in middle school and adjustment several years later, by the end of high school, among upper middle class youth. Prior research has shown negative reputations such as aggressive-disruptive and sensitive-isolated to be associated with maladjustment later in life, whereas reputations like popular and prosocial-leader have been related to positive future outcomes. However, there are contrary findings that reveal a more complex relationship between peer reputation and adjustment, showing certain “negative” reputations to be tied with better outcomes in some domains and the converse in others. Using a sample of middle school students, a confirmatory factor analysis (CFA) was performed to test a four-factor model of the Revised Class Play, a peer report measure on peer reputations. CFA findings supported the four-factor model with the following reputations: popular, prosocial, aggressive, and isolated. Structural equation models were used to predict 12th grade adjustment outcomes (academic achievement, psychopathology, substance use) from middle school peer reputation. Prosocial reputation in middle school was connected to higher academic achievement and fewer externalizing symptoms in 12th grade. Both prosocial and isolated peer reputation were negatively associated with alcohol, cigarette, and marijuana use, whereas a popular reputation was related to higher levels of alcohol use. Middle school reputation did not predict internalizing symptoms in 12th grade. Findings are discussed in terms of adaptive and maladaptive adjustment outcomes associated with each peer reputation and implications for future research.
ContributorsCurlee, Alexandria (Author) / Luthar, Suniya (Thesis advisor) / Aiken, Leona (Committee member) / Infurna, Frank (Committee member) / Arizona State University (Publisher)
Created2016
Description
Purpose: Over-identification of Navajo Head Start children into special education on the Navajo Reservation has come to the attention of Tribal leaders, Educational leaders, and parents due to the use of invalid assessment measures. Dynamic assessment (DA) of narratives may be a tool for distinguishing language differences from language disorders. The purpose of this study is to determine whether the Predictive Early Assessment of Reading and Language (PEARL), a dynamic assessment of narratives, accurately classifies Navajo Head Start students with typically developing (TD) language or with language impairment (LI), and to examine which measures best predict children’s overall performances on the PEARL.
Method: Ninety, 4- and 5-year-old Navajo preschoolers with LI and with TD language were selected. Children completed the PEARL, which measured both language comprehension and production using pretest and posttest scores, and a modifiability scale. In addition, children completed the Clinical Evaluation of Language Fundamental, Preschool, Second Edition (CELF – Preschool 2) and language samples. A Navajo Speech Language Pathologist confirmed the diagnosis of the participants. Research assistants pretested, briefly taught the principles of narrative structure (story grammar, language complexity and episode) and evaluated response to learning using an index of modifiability.
Results: Results of discriminant analysis indicated that PEARL pretest differentiated both ability groups with 89% accuracy. In addition, posttest scores discriminated with 89% accuracy and modifiability scores with 100% accuracy. Further, the subtest story grammar was the best predictor at pretest and posttest, although modifiability scores were better predictors of both ability groups.
Conclusion: Findings indicate that the PEARL is a promising assessment for accurately differentiating Navajo preschool children with LI from Navajo preschool children with TD language. The PEARL’s recommended pretest cut score over-identified Navajo children with TD language; therefore, a new recommended cut score was determined.
Method: Ninety, 4- and 5-year-old Navajo preschoolers with LI and with TD language were selected. Children completed the PEARL, which measured both language comprehension and production using pretest and posttest scores, and a modifiability scale. In addition, children completed the Clinical Evaluation of Language Fundamental, Preschool, Second Edition (CELF – Preschool 2) and language samples. A Navajo Speech Language Pathologist confirmed the diagnosis of the participants. Research assistants pretested, briefly taught the principles of narrative structure (story grammar, language complexity and episode) and evaluated response to learning using an index of modifiability.
Results: Results of discriminant analysis indicated that PEARL pretest differentiated both ability groups with 89% accuracy. In addition, posttest scores discriminated with 89% accuracy and modifiability scores with 100% accuracy. Further, the subtest story grammar was the best predictor at pretest and posttest, although modifiability scores were better predictors of both ability groups.
Conclusion: Findings indicate that the PEARL is a promising assessment for accurately differentiating Navajo preschool children with LI from Navajo preschool children with TD language. The PEARL’s recommended pretest cut score over-identified Navajo children with TD language; therefore, a new recommended cut score was determined.
ContributorsHenderson, Davis E (Author) / Restrepo, Maria Adelaida (Thesis advisor) / Aiken, Leona (Committee member) / Petersen, Douglas (Committee member) / Romero-Little, Mary Eunice (Committee member) / Kleinsasser, Robert (Committee member) / Arizona State University (Publisher)
Created2017
Description
In investigating mediating processes, researchers usually use randomized experiments and linear regression or structural equation modeling to determine if the treatment affects the hypothesized mediator and if the mediator affects the targeted outcome. However, randomizing the treatment will not yield accurate causal path estimates unless certain assumptions are satisfied. Since randomization of the mediator may not be plausible for most studies (i.e., the mediator status is not randomly assigned, but self-selected by participants), both the direct and indirect effects may be biased by confounding variables. The purpose of this dissertation is (1) to investigate the extent to which traditional mediation methods are affected by confounding variables and (2) to assess the statistical performance of several modern methods to address confounding variable effects in mediation analysis. This dissertation first reviewed the theoretical foundations of causal inference in statistical mediation analysis, modern statistical analysis for causal inference, and then described different methods to estimate causal direct and indirect effects in the presence of two post-treatment confounders. A large simulation study was designed to evaluate the extent to which ordinary regression and modern causal inference methods are able to obtain correct estimates of the direct and indirect effects when confounding variables that are present in the population are not included in the analysis. Five methods were compared in terms of bias, relative bias, mean square error, statistical power, Type I error rates, and confidence interval coverage to test how robust the methods are to the violation of the no unmeasured confounders assumption and confounder effect sizes. The methods explored were linear regression with adjustment, inverse propensity weighting, inverse propensity weighting with truncated weights, sequential g-estimation, and a doubly robust sequential g-estimation. Results showed that in estimating the direct and indirect effects, in general, sequential g-estimation performed the best in terms of bias, Type I error rates, power, and coverage across different confounder effect, direct effect, and sample sizes when all confounders were included in the estimation. When one of the two confounders were omitted from the estimation process, in general, none of the methods had acceptable relative bias in the simulation study. Omitting one of the confounders from estimation corresponded to the common case in mediation studies where no measure of a confounder is available but a confounder may affect the analysis. Failing to measure potential post-treatment confounder variables in a mediation model leads to biased estimates regardless of the analysis method used and emphasizes the importance of sensitivity analysis for causal mediation analysis.
ContributorsKisbu Sakarya, Yasemin (Author) / Mackinnon, David Peter (Thesis advisor) / Aiken, Leona (Committee member) / West, Stephen (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2013
Description
Specific cultural variables have been found to protect against the onset of alcohol, tobacco and drug use among Latino adolescents. It has been suggested that targeting similar cultural components during the treatment of drug dependence and abuse for Latino adults may also enhance the effectiveness of the intervention, although few studies have explored this hypothesis. The current study attempted to remedy this disparity by exploring the potentially protective influence of two cultural variables, ethnic pride and family traditionalism, on self-efficacy to avoid drug use following residential substance abuse treatment among 99 Hispanic and 85 non-Hispanic White males. Results of the study indicate that higher levels of ethnic pride predict greater confidence to remain abstinent from drugs following substance abuse treatment, and that this relationship is stronger among Hispanic participants than non-Hispanic White participants. Family traditionalism was not a significant predictor of drug avoidance self-efficacy for either group, suggesting that some specific cultural variables may be better targets for substance abuse treatment than others. Study limitations and future directions for research and clinical practice are discussed.
ContributorsBoyd, Stephen James (Author) / Gonzalez Castro, Felipe (Thesis advisor) / Barrera, Jr., Manuel (Committee member) / Aiken, Leona (Committee member) / Arizona State University (Publisher)
Created2011
Description
We constructed an 11-arm, walk-through, human radial-arm maze (HRAM) as a translational instrument to compare existing methodology in the areas of rodent and human learning and memory research. The HRAM, utilized here, serves as an intermediary test between the classic rat radial-arm maze (RAM) and standard human neuropsychological and cognitive tests. We show that the HRAM is a useful instrument to examine working memory ability, explore the relationships between rodent and human memory and cognition models, and evaluate factors that contribute to human navigational ability. One-hundred-and-fifty-seven participants were tested on the HRAM, and scores were compared to performance on a standard cognitive battery focused on episodic memory, working memory capacity, and visuospatial ability. We found that errors on the HRAM increased as working memory demand became elevated, similar to the pattern typically seen in rodents, and that for this task, performance appears similar to Miller's classic description of a processing-inclusive human working memory capacity of 7 ± 2 items. Regression analysis revealed that measures of working memory capacity and visuospatial ability accounted for a large proportion of variance in HRAM scores, while measures of episodic memory and general intelligence did not serve as significant predictors of HRAM performance. We present the HRAM as a novel instrument for measuring navigational behavior in humans, as is traditionally done in basic science studies evaluating rodent learning and memory, thus providing a useful tool to help connect and translate between human and rodent models of cognitive functioning.
ContributorsMennenga, Sarah (Author) / Baxter, Leslie C. (Author) / Grunfeld, Itamar (Author) / Brewer, Gene (Author) / Aiken, Leona (Author) / Engler-Chiurazzi, Elizabeth (Author) / Camp, Bryan (Author) / Acosta, Jazmin (Author) / Braden, B. Blair (Author) / Schaefer, Keley (Author) / Gerson, Julia (Author) / Lavery, Courtney (Author) / Tsang, Candy (Author) / Hewitt, Lauren (Author) / Kingston, Melissa L. (Author) / Koebele, Stephanie (Author) / Patten, Kristopher (Author) / Ball, B. Hunter (Author) / McBeath, Michael (Author) / Bimonte-Nelson, Heather (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-09-09
Description
The present study tested the respective mediating effects of sensation seeking and initial level of response (LR) to negative, sedative alcohol effects on the relation between the density of familial history of alcoholism and adolescent alcohol use. Additionally, the present study tested the direct effect of LR to negative, sedative alcohol effects on adolescent drinking over and above the effects of sensation seeking; and also tested the moderating effect of sensation seeking on the relation between level of response negative, sedative alcohol effects and adolescent drinking. Specifically, OLS regression models first estimated the effects of sensation seeking, LR to negative, sedative alcohol effects, and their interaction on alcohol outcomes, over and above the influence of covariates. Indirect effects were then tested using the PRODCLIN method through RMediation. Analyses failed to support sensation seeking as a mediator in the relation between familial history of alcoholism and adolescent drinking, and as a moderator of the relation between LR and adolescent drinking. However, analyses did support a robust direct effect of LR to negative, sedative alcohol effects on adolescent alcohol involvement. A significant mediating effect of initial LR to negative, sedative alcohol effects on the relation between familial alcoholism and adolescent drinking was found, however failed to maintain significance in post-hoc analyses attenuating the downward bias of the measure of initial LR. Initial LR to negative, sedative alcohol effects continued to predict adolescent drinking after attenuating measure bias. These findings strengthen research on initial LR to negative, sedative alcohol effects as a risk for greater alcohol involvement in adolescence, and underscore the complexity of studying the familial transmission of alcoholism in adolescent populations
ContributorsPandika, Danielle (Author) / Chassin, Laurie (Thesis advisor) / Corbin, William (Committee member) / Aiken, Leona (Committee member) / Arizona State University (Publisher)
Created2015
Description
Women are exposed to numerous endogenous and exogenous hormones across the lifespan. In the last several decades, the prescription of novel hormonal contraceptives and hormone therapies (HTs) have resulted in aging women that have a unique hormone exposure history; little is known about the impact of these hormone exposures on short- and long- term brain health. The goal of my dissertation was to understand how lifetime hormone exposures shape the female cognitive phenotype using several innovative approaches, including a new human spatial working memory task, the human radial arm maze (HRAM), and several rodent menopause models with variants of clinically used hormone treatments. Using the HRAM (chapter 2) and established human neuropsychological tests, I determined males outperformed females with high endogenous or exogenous estrogen levels on visuospatial tasks and the spatial working memory HRAM (chapter 3). Evaluating the synthetic estrogen in contraceptives, ethinyl estradiol (EE), I found a high EE dose impaired spatial working memory in ovariectomized (Ovx) rats, medium and high EE doses reduced choline-acetyltransferace-immunoreactive neuron population estimates in the basal forebrain following Ovx (chapter 4), and low EE impaired spatial cognition in ovary-intact rats (chapter 5). Assessing the impact of several clinically-used HTs, I identified a window of opportunity around ovarian follicular depletion outside of which the HT conjugated equine estrogens (CEE) was detrimental to spatial memory (chapter 6), as well as therapeutic potentials for synthetic contraceptive hormones (chapter 9) and bioidentical estradiol (chapter 7) during and after the transition to menopause. Chapter 6 and 7 findings, that estradiol and Ovx benefitted cognition after the menopause transition, but CEE did not, are perhaps due to the negative impact of ovarian-produced, androstenedione-derived estrone; indeed, blocking androstenedione’s conversion to estrone prevented its cognitive impairments (chapter 8). Finally, I determined that EE combined with the popular progestin levonorgestrel benefited spatial memory during the transition to menopause, a profile not seen with estradiol, levonorgestrel, or EE alone (chapter 9). This work identifies several cognitively safe, and enhancing, hormonal treatment options at different time points throughout female aging, revealing promising avenues toward optimizing female health.
ContributorsMennenga, Sarah E (Author) / Bimonte-Nelson, Heather A. (Thesis advisor) / Aiken, Leona (Committee member) / Whiteaker, Paul (Committee member) / Talboom, Joshua (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of this study was to examine in which way adding more indicators or a covariate influences the performance of latent class analysis (LCA). We varied the sample size (100 ≤ N ≤ 2000), number, and quality of binary indicators (between 4 and 12 indicators with conditional response probabilities of [0.3, 0.7], [0.2, 0.8], or [0.1, 0.9]), and the strength of covariate effects (zero, small, medium, large) in a Monte Carlo simulation study of 2- and 3-class models. The results suggested that in general, a larger sample size, more indicators, a higher quality of indicators, and a larger covariate effect lead to more converged and proper replications, as well as fewer boundary parameter estimates and less parameter bias. Furthermore, interactions among these study factors demonstrated how using more or higher quality indicators, as well as larger covariate effect size, could sometimes compensate for small sample size. Including a covariate appeared to be generally beneficial, although the covariate parameters themselves showed relatively large bias. Our results provide useful information for practitioners designing an LCA study in terms of highlighting the factors that lead to better or worse performance of LCA.
ContributorsWurpts, Ingrid Carlson (Author) / Geiser, Christian (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-08-21