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- All Subjects: Mediation
- All Subjects: public health
Description
Including a covariate can increase power to detect an effect between two variables. Although previous research has studied power in mediation models, the extent to which the inclusion of a mediator will increase the power to detect a relation between two variables has not been investigated. The first study identified situations where empirical and analytical power of two tests of significance for a single mediator model was greater than power of a bivariate significance test. Results from the first study indicated that including a mediator increased statistical power in small samples with large effects and in large samples with small effects. Next, a study was conducted to assess when power was greater for a significance test for a two mediator model as compared with power of a bivariate significance test. Results indicated that including two mediators increased power in small samples when both specific mediated effects were large and in large samples when both specific mediated effects were small. Implications of the results and directions for future research are then discussed.
ContributorsO'Rourke, Holly Patricia (Author) / Mackinnon, David P (Thesis advisor) / Enders, Craig K. (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2013
Description
Sexual risk taking is prevalent in adolescence, particularly among Latino teens, and can have serious consequences in the form of contraction of STIs, HIV, and increased risk of unintended pregnancy. Family contexts characterized by conflict and lack of support are antecedents of adolescent sexual risk taking, but evidence elucidating the mechanisms underlying this association is lacking. The current study sought to test two potential pathways to sexual risk taking within the framework of social developmental theory, among a sample of 189 Mexican origin adolescents and their caregivers interviewed in the 7th, 8th, and 12th grades. Structural equation modeling was utilized to examine pathways from 7th grade family risk to age of sexual initiation, number of lifetime sexual partners, and condom nonuse reported in the 12th grade. Deviant peer affiliations and academic engagement at 8th grade were tested as mediators of this relationship for boys and girls. Results confirm the importance of the family context, with family risk exerting direct effects on the number of lifetime sexual partners for both genders, and on age of sexual initiation for females only. Deviant peer affiliations serve as a mediator of family risk for males, but not females. When included in a model alongside deviant peers, academic engagement does not play the hypothesized mediating role between family risk and any of the sexual risk outcomes. Future research ought to consider additional mediators that better account for the relation between family risk and sexual risk taking among females.
ContributorsJensen, Michaeline R (Author) / Gonzales, Nancy A. (Thesis advisor) / Lopez, Vera (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2012
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