Matching Items (4)
Filtering by
- All Subjects: Intellectual Disability
- All Subjects: Mediation (Statistics)
- 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
Family plays an important yet understudied role in the development of psychopathology during childhood, particularly for children at developmental risk. Indeed, much of the research on families has actually concentrated more on risk processes in individual family members or within-family subsystems. In general, important and complex associations have been found among family-related constructs such as marital conflict, parent-child relationships, parental depression, and parenting stress, which have in turn been found to contribute to the emergence of children's behavioral problems. Research has begun to emerge that certain family system constructs, such as cohesion, organization, and control may influence children's development, but this research has been limited by a focus on parent-reports of family functioning, rather than utilizing observational methods. With notable exceptions, there is almost no observational research examining families of children at developmental risk. This study examined the longitudinal relations among family risk and family system constructs, as well as how family systems constructs mediated the relations between family risk and child outcome. Further, the study examined how developmental risk moderated these relations. The sample followed 242 families of children with and without developmental risk across the transition-to-school period. Family risk factors were assessed at 5 years, using parental reports of symptomatology, parenting stress, and marital adjustment, and observational assessments of the parent-child relationship. Family system constructs (cohesion, warmth, conflict, organization, control) were measured at age 6 using structured observations of the entire family playing a board game. Child behavior problems and social competence were assessed at age 7. Results indicated that families of children with developmental delays did not differ from families of typically developing children on the majority of family system attributes. Cohesion and organization mediated the relations between specific family risk factors and social competence for all families. For families of typically developing children only, higher levels of control were associated with more behavior problems and less social competence. These findings underscore the importance of family-level assessment in understanding the development of psychopathology. Important family effects on children's social competence were found, although the pathways among family risk and family systems attributes are complex.
ContributorsGerstein, Emily Davis (Author) / Crnic, Keith A (Thesis advisor) / Aiken, Leona (Committee member) / Bradley, Robert (Committee member) / Gonzales, Nancy (Committee member) / Arizona State University (Publisher)
Created2012
Description
The aim of this study was to examine the effects of Assisted Cycle Therapy (ACT) on self-efficacy and exercise perception in older adults with Down syndrome (DS) after a three times a week for 8 weeks intervention. Thirteen participants were in the ACT group in which a motor assisted their cycling to be performed at least 30% faster than voluntary cycling (VC), 11 participants were in the voluntary cycling group and two participants were in the no cycling (NC) group. The results showed that both exercise groups (i.e., ACT and VC) improved in their self-efficacy after the 8 week intervention. In addition, exercise perception improved following ACT and not VC or NC. Our results are discussed with respect to their future implications for exercise in the DS population. It might be that the yielded results were due to differences in effort required by each intervention group as well as the neurotrophic factors that occur when muscle contractions create synaptic connections resulting in improvement in cognition and feelings of satisfaction. In the future, research should focus on the psychological factors such as social accountability and peer interaction as they relate to ACT and physical activity in person's with DS.
ContributorsTucker, Kori Ann (Author) / Ringenbach, Shannon (Thesis director) / Arnold, Nathaniel (Committee member) / Holzapfel, Simon (Committee member) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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