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- All Subjects: Psychology, Behavioral
Description
Methods to test hypotheses of mediated effects in the pretest-posttest control group design are understudied in the behavioral sciences (MacKinnon, 2008). Because many studies aim to answer questions about mediating processes in the pretest-posttest control group design, there is a need to determine which model is most appropriate to test hypotheses about mediating processes and what happens to estimates of the mediated effect when model assumptions are violated in this design. The goal of this project was to outline estimator characteristics of four longitudinal mediation models and the cross-sectional mediation model. Models were compared on type 1 error rates, statistical power, accuracy of confidence interval coverage, and bias of parameter estimates. Four traditional longitudinal models and the cross-sectional model were assessed. The four longitudinal models were analysis of covariance (ANCOVA) using pretest scores as a covariate, path analysis, difference scores, and residualized change scores. A Monte Carlo simulation study was conducted to evaluate the different models across a wide range of sample sizes and effect sizes. All models performed well in terms of type 1 error rates and the ANCOVA and path analysis models performed best in terms of bias and empirical power. The difference score, residualized change score, and cross-sectional models all performed well given certain conditions held about the pretest measures. These conditions and future directions are discussed.
ContributorsValente, Matthew John (Author) / MacKinnon, David (Thesis advisor) / West, Stephen (Committee member) / Aiken, Leona (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2015
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
Children's academic experiences during first grade have substantial implications for their academic performance both concurrently and longitudinally. Using two complementary studies, this dissertation utilizing data from the National Institute of Child Development Study of Early Child Care and Youth Development helps create a better understanding of the importance of first-grade experiences for children's academic performance. The first study expands upon current literature by focusing on how children's academic experiences simultaneously influence children's academic performance through behavioral engagement. Specifically, study one examined the mediating role of first-grade behavioral engagement between first-grade academic experiences (i.e. parental involvement, positive peer interactions, student-teacher relationship, and instructional support) and second-grade academic performance. Using a panel model, results showed that behavioral engagement mediates relations between peer interactions and academic performance and relations between instructional support and academic performance. Implications for interventions focusing on children's positive peer interactions and teacher's high-quality instructional support in order to promote behavioral engagement during early elementary school are discussed.
The second study expands the current literature regarding instructional quality thresholds. Limited research has addressed the question of whether there is a minimum level of instructional quality that must be experienced in order to see significant changes in children's academic performance, and the limited research has focused primarily on preschoolers. The goal of study two was to determine if high-quality first-grade instructional support predicted children's first-, third-, and fifth-grade academic performance. Using piecewise regression analyses, results did not show evidence of a relation between first-grade instructional support quality and children's academic performance at any grade. Possible reasons for inconsistencies in findings from this study and previous research are discussed, including differences in sample characteristics and measurement tools. Because instructional quality remains at the forefront of discussions by educators and policy makers, the inconsistencies in research findings argue for further research that may clarify thresholds of instructional support quality that must be met in order for various subgroups of children to gain the skills needed for long-term academic success.
The second study expands the current literature regarding instructional quality thresholds. Limited research has addressed the question of whether there is a minimum level of instructional quality that must be experienced in order to see significant changes in children's academic performance, and the limited research has focused primarily on preschoolers. The goal of study two was to determine if high-quality first-grade instructional support predicted children's first-, third-, and fifth-grade academic performance. Using piecewise regression analyses, results did not show evidence of a relation between first-grade instructional support quality and children's academic performance at any grade. Possible reasons for inconsistencies in findings from this study and previous research are discussed, including differences in sample characteristics and measurement tools. Because instructional quality remains at the forefront of discussions by educators and policy makers, the inconsistencies in research findings argue for further research that may clarify thresholds of instructional support quality that must be met in order for various subgroups of children to gain the skills needed for long-term academic success.
ContributorsBryce, Crystal I (Author) / Bradley, Robert H (Thesis advisor) / Abry, Tashia (Committee member) / Swanson, Jodi (Committee member) / Thompson, Marilyn S (Committee member) / Arizona State University (Publisher)
Created2015
Description
The purpose of this study was to examine under which conditions "good" data characteristics can compensate for "poor" characteristics in Latent Class Analysis (LCA), as well as to set forth guidelines regarding the minimum sample size and ideal number and quality of indicators. In particular, we studied to which extent including a larger number of high quality indicators can compensate for a small sample size in LCA. The results suggest that in general, larger sample size, more indicators, higher quality of indicators, and a larger covariate effect correspond to more converged and proper replications, as well as fewer boundary estimates and less parameter bias. Based on the results, it is not recommended to use LCA with sample sizes lower than N = 100, and to use many high quality indicators and at least one strong covariate when using sample sizes less than N = 500.
ContributorsWurpts, Ingrid Carlson (Author) / Geiser, Christian (Thesis advisor) / Aiken, Leona (Thesis advisor) / West, Stephen (Committee member) / Arizona State University (Publisher)
Created2012
Description
This study examined the influence of childhood aggression, peer exclusion and associating with deviant peers on the development of antisocial behavior in early adolescence. To gain a stronger understanding of how these factors are associated with antisocial behavior and delinquency, multiple alternative pathways were examined based on additive, mediation and incidental models. A parallel process growth model was specified to assess whether early childhood aggression and peer exclusion (in 1st grade) and intra-individual increases in aggressive behaviors and exclusion through childhood (grades 1 to 6) are predictive of associating with deviant peers (in 7th grade) and antisocial behavior (in 8th grade). Based on a sample of 383 children (193 girls and 190 boys), results showed the strongest support for an additive effects model in which early childhood aggression, increases in aggression, increases in peer exclusion and associating with more deviant peers all predicted antisocial behavior. These findings have implications for how children's psychological adjustment is impacted by their behavioral propensities and peer relational context and the importance of examining developmental processes within and between children over time.
ContributorsEttekal, Idean (Author) / Ladd, Gary W (Thesis advisor) / Eggum, Natalie D (Committee member) / Thompson, Marilyn S (Committee member) / Arizona State University (Publisher)
Created2011
Description
Evidence thus far has not lent credence to facilitate lie detection by the average person. According to studies, there are five major signs of lying: lip pursing, narrowed eyebrows, shoulder shrugs, looking to the left, and smirking. The present study aims to determine whether training people in detecting the five signs of lying will facilitate lie detection in the average person. We analyzed the accuracy of lie detection by examining the verdicts of 155 undergraduate students during simulated police interrogations. Comparisons between the trained and untrained subjects support the hypothesis that the average person is no better than chance at detecting lies through non-verbal cues.
ContributorsRivera, Aylin Melissa (Author) / Lanyon, Richard (Thesis director) / Aiken, Leona (Committee member) / Barrett, The Honors College (Contributor) / School of Criminology and Criminal Justice (Contributor) / Department of Psychology (Contributor)
Created2014-12
Description
There are significant and wide-ranging health benefits of physical activity, yet the majority of adolescents in the United States do not engage in the recommended amount. This poses a significant public health challenge. Parents have a substantial influence on adolescents' levels of activity, indicating that parenting may be an especially salient target of interventions designed to promote physical activity. The current study tested the hypothesis that a family intervention to promote effective parenting would have a positive collateral effect on adolescent physical activity. This study also tested whether the increase in activity was mediated by changes in parental monitoring and family relationship quality. Furthermore, the current study assessed whether adolescent gender moderated the relationship between parental monitoring and physical activity, such that increased parental monitoring predicted increases in physical activity for girls, but not for boys. Participants were 232 adolescents at risk for behavior problems drawn from a larger randomized controlled trial of the Family Check-Up. Adolescents completed questionnaires and participated in a family assessment with their caregivers in the 6th through 9th grades. Youth randomized to the intervention reported significantly more physical activity at follow-up relative to controls. Results failed to confirm the role of family factors as mediators of the effect of the intervention on physical activity. When gender was considered as a moderator, it appeared that parental monitoring was strongly and positively correlated with physical activity for girls, but not for boys. While the mechanism by which the Family Check-Up leads to increased physical activity remains unclear, its robust effects suggest that family intervention can be used to promote physical activity and might therefore have further-reaching health benefits.
ContributorsRudo-Stern, Jenna (Author) / Dishion, Thomas J (Thesis advisor) / Wolchik, Sharlene (Committee member) / Aiken, Leona (Committee member) / Arizona State University (Publisher)
Created2015
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
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