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- All Subjects: Psychology--Statistical methods.
- All Subjects: Substance abuse
- Creators: Aiken, Leona
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
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
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
Brave Bears was a Barrett creative project that operated under local non-profit organizations, Amanda Hope Rainbow Angels and Arizona Women’s Recovery Center. Amanda Hope Rainbow Angels provides support and education for children fighting cancer and their families. Arizona Women’s Recovery Center provides rehabilitation programs for women fighting substance abuse and housing for the women and their children. The Brave Bears Project was focused on helping children in these situations cope with the trauma they are experiencing. The children received a teddy bear, which is a transitional object. In addition, a clay pendant with the word, “brave” pressed into it was tied around the bear’s neck with a ribbon. A poem of explanation and encouragement was also included.<br/><br/>The teddy bear provided comfort to children experiencing emotionally distressing situations as they receive treatment for their illness or as their mom undergoes rehabilitation. This can be in the form of holding the teddy bear when they feel frightened, anxious, lonely or depressed. The “brave” pendant and poem seek to encourage them and acknowledge their trauma and ability to persevere.
ContributorsRichards, Emma Joy (Author) / Lopez, Kristina (Thesis director) / Safyer, Paige (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05