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- All Subjects: Psychology--Statistical methods.
- All Subjects: Family
- 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
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
Background: It is estimated that 50% of all mental illness arises prior to age 14, an incident attributed in part to disruptions and imbalances within the family system. Equine assisted learning is a complementary and alternative approach to family therapy which is being used increasingly to promote mental health in both adults and children. This study sought to build and deliver an evidence-based, family-centered equine assisted learning program aimed at promoting family function, family satisfaction and child social-emotional competence, and to measure its acceptability and preliminary effect.
Method: Twenty families with children 10 years and older were recruited to participate in a 3-week equine assisted learning program at a therapeutic riding center in Phoenix, Arizona. Sessions included groundwork activities with horses used to promote life skills using experiential learning theory. The study design included a mixed-method quasi-experimental one-group pretest posttest design using the following mental health instruments: Devereaux Student Strengths Assessment, Brief Family Assessment Measure (3 dimensions), and Family Satisfaction Scale to measure child social-emotional competence, family function, and family satisfaction, respectively. Acceptability was determined using a Likert-type questionnaire with open-ended questions to gain a qualitative thematic perspective of the experience.
Results: Preliminary pretest and posttest comparisons were statistically significant for improvements in family satisfaction (p = 0.001, M = -5.84, SD = 5.63), all three domains of family function (General Scale: p = 0.005, M = 6.84, SD = 9.20; Self-Rating Scale: p = 0.050, M = 6.53, SD = 12.89; and Dyadic Relationship Scale: p = 0.028, M = 3.47, SD = 7.18), and child social-emotional competence (p = 0.015, M = -4.05, SD 5.95). Effect sizes were moderate to large (d > 0.5) for all but one instrument (Self-Rating Scale), suggesting a considerable magnitude of change over the three-week period. The intervention was highly accepted among both children and adults. Themes of proximity, self-discovery, and regard for others emerged during evaluation of qualitative findings. Longitudinal comparisons of baseline and 3-month follow-up remain in-progress, a topic available for future discussion.
Discussion: Results help to validate equine assisted learning as a valuable tool in the promotion of child social-emotional intelligence strengthened in part by the promotion of family function and family satisfaction. For mental health professionals, these results serve as a reminder of the alternatives that are available, as well as the importance of partnerships within the community. For therapeutic riding centers, these results help equine professionals validate their programs and gain a foothold within the scientific community. Additionally, they invite future riding centers to follow course in incorporating evidence into their programs and examining new directions for growth within the mental health community.
Method: Twenty families with children 10 years and older were recruited to participate in a 3-week equine assisted learning program at a therapeutic riding center in Phoenix, Arizona. Sessions included groundwork activities with horses used to promote life skills using experiential learning theory. The study design included a mixed-method quasi-experimental one-group pretest posttest design using the following mental health instruments: Devereaux Student Strengths Assessment, Brief Family Assessment Measure (3 dimensions), and Family Satisfaction Scale to measure child social-emotional competence, family function, and family satisfaction, respectively. Acceptability was determined using a Likert-type questionnaire with open-ended questions to gain a qualitative thematic perspective of the experience.
Results: Preliminary pretest and posttest comparisons were statistically significant for improvements in family satisfaction (p = 0.001, M = -5.84, SD = 5.63), all three domains of family function (General Scale: p = 0.005, M = 6.84, SD = 9.20; Self-Rating Scale: p = 0.050, M = 6.53, SD = 12.89; and Dyadic Relationship Scale: p = 0.028, M = 3.47, SD = 7.18), and child social-emotional competence (p = 0.015, M = -4.05, SD 5.95). Effect sizes were moderate to large (d > 0.5) for all but one instrument (Self-Rating Scale), suggesting a considerable magnitude of change over the three-week period. The intervention was highly accepted among both children and adults. Themes of proximity, self-discovery, and regard for others emerged during evaluation of qualitative findings. Longitudinal comparisons of baseline and 3-month follow-up remain in-progress, a topic available for future discussion.
Discussion: Results help to validate equine assisted learning as a valuable tool in the promotion of child social-emotional intelligence strengthened in part by the promotion of family function and family satisfaction. For mental health professionals, these results serve as a reminder of the alternatives that are available, as well as the importance of partnerships within the community. For therapeutic riding centers, these results help equine professionals validate their programs and gain a foothold within the scientific community. Additionally, they invite future riding centers to follow course in incorporating evidence into their programs and examining new directions for growth within the mental health community.
ContributorsSolarz, Allison (Author) / Chen, Angela (Thesis advisor)
Created2019-05-02