Matching Items (4)
Filtering by
- All Subjects: Divorce
- All Subjects: Quantitative Psychology and Psychometrics
- Creators: Tein, Jenn-Yun
Description
Random Forests is a statistical learning method which has been proposed for propensity score estimation models that involve complex interactions, nonlinear relationships, or both of the covariates. In this dissertation I conducted a simulation study to examine the effects of three Random Forests model specifications in propensity score analysis. The results suggested that, depending on the nature of data, optimal specification of (1) decision rules to select the covariate and its split value in a Classification Tree, (2) the number of covariates randomly sampled for selection, and (3) methods of estimating Random Forests propensity scores could potentially produce an unbiased average treatment effect estimate after propensity scores weighting by the odds adjustment. Compared to the logistic regression estimation model using the true propensity score model, Random Forests had an additional advantage in producing unbiased estimated standard error and correct statistical inference of the average treatment effect. The relationship between the balance on the covariates' means and the bias of average treatment effect estimate was examined both within and between conditions of the simulation. Within conditions, across repeated samples there was no noticeable correlation between the covariates' mean differences and the magnitude of bias of average treatment effect estimate for the covariates that were imbalanced before adjustment. Between conditions, small mean differences of covariates after propensity score adjustment were not sensitive enough to identify the optimal Random Forests model specification for propensity score analysis.
ContributorsCham, Hei Ning (Author) / Tein, Jenn-Yun (Thesis advisor) / Enders, Stephen G (Thesis advisor) / Enders, Craig K. (Committee member) / Mackinnon, David P (Committee member) / Arizona State University (Publisher)
Created2013
Description
An ever expanding body of research has shown that children of divorce are at increased risk for a range of maladaptive outcomes including academic failure, behavior problems, poor psychological adjustment, reduced self-concept, and reduced social competence (Amato, 2001). Furthermore, the widespread prevalence of divorce makes preventing these poor outcomes a pressing public health concern. The Children of Divorce-Coping with Divorce (CoD-CoD) program is an internet-based selective prevention that was derived from recent research identifying modifiable protective factors in children of divorce including active and avoidant coping, divorce appraisals, and coping efficacy. CoD-CoD addresses these putative mediators through careful adaptation of intervention components previously demonstrated to be effective for children from disrupted families (Pedro-Carroll & Alpert-Gillis, 1997; Stolberg & Mahler, 1994; Sandler, et al., 2003). In the CoD-CoD efficacy trial, 147 children ages 11-16 whose family had received a divorce decree within 48 months of the intervention start date served as participants. Participants were assessed in two waves in order to test the small theory of the intervention as well as the interventions effects on internalizing and externalizing behaviors. Analyses indicated that the program effectively reduced the participants total mental health problems and emotional problems as reported on the Strengths and Difficulties Questionnaire (SDQ) (d = .37) and for total mental health problems this effect was stronger for children with greater baseline mental health problems (d = .46). The program also had mediated effects on both child and parent-reported total mental health problems whereby the program improved coping efficacy for children with low baseline coping efficacy which led to reduced parent-reported mental health problems. To the author's knowledge this is the first randomized controlled trail of internet-based mental health program for children or adolescents which utilizes an active control condition.
ContributorsBoring, Jesse (Author) / Sandler, Irwin (Thesis advisor) / Crnic, Keith (Committee member) / Tein, Jenn-Yun (Committee member) / Horan, John (Committee member) / Arizona State University (Publisher)
Created2011
Description
This dissertation examines a planned missing data design in the context of mediational analysis. The study considered a scenario in which the high cost of an expensive mediator limited sample size, but in which less expensive mediators could be gathered on a larger sample size. Simulated multivariate normal data were generated from a latent variable mediation model with three observed indicator variables, M1, M2, and M3. Planned missingness was implemented on M1 under the missing completely at random mechanism. Five analysis methods were employed: latent variable mediation model with all three mediators as indicators of a latent construct (Method 1), auxiliary variable model with M1 as the mediator and M2 and M3 as auxiliary variables (Method 2), auxiliary variable model with M1 as the mediator and M2 as a single auxiliary variable (Method 3), maximum likelihood estimation including all available data but incorporating only mediator M1 (Method 4), and listwise deletion (Method 5).
The main outcome of interest was empirical power to detect the mediated effect. The main effects of mediation effect size, sample size, and missing data rate performed as expected with power increasing for increasing mediation effect sizes, increasing sample sizes, and decreasing missing data rates. Consistent with expectations, power was the greatest for analysis methods that included all three mediators, and power decreased with analysis methods that included less information. Across all design cells relative to the complete data condition, Method 1 with 20% missingness on M1 produced only 2.06% loss in power for the mediated effect; with 50% missingness, 6.02% loss; and 80% missingess, only 11.86% loss. Method 2 exhibited 20.72% power loss at 80% missingness, even though the total amount of data utilized was the same as Method 1. Methods 3 – 5 exhibited greater power loss. Compared to an average power loss of 11.55% across all levels of missingness for Method 1, average power losses for Methods 3, 4, and 5 were 23.87%, 29.35%, and 32.40%, respectively. In conclusion, planned missingness in a multiple mediator design may permit higher quality characterization of the mediator construct at feasible cost.
The main outcome of interest was empirical power to detect the mediated effect. The main effects of mediation effect size, sample size, and missing data rate performed as expected with power increasing for increasing mediation effect sizes, increasing sample sizes, and decreasing missing data rates. Consistent with expectations, power was the greatest for analysis methods that included all three mediators, and power decreased with analysis methods that included less information. Across all design cells relative to the complete data condition, Method 1 with 20% missingness on M1 produced only 2.06% loss in power for the mediated effect; with 50% missingness, 6.02% loss; and 80% missingess, only 11.86% loss. Method 2 exhibited 20.72% power loss at 80% missingness, even though the total amount of data utilized was the same as Method 1. Methods 3 – 5 exhibited greater power loss. Compared to an average power loss of 11.55% across all levels of missingness for Method 1, average power losses for Methods 3, 4, and 5 were 23.87%, 29.35%, and 32.40%, respectively. In conclusion, planned missingness in a multiple mediator design may permit higher quality characterization of the mediator construct at feasible cost.
ContributorsBaraldi, Amanda N (Author) / Enders, Craig K. (Thesis advisor) / Mackinnon, David P (Thesis advisor) / Aiken, Leona S. (Committee member) / Tein, Jenn-Yun (Committee member) / Arizona State University (Publisher)
Created2015
Description
This study examined whether the New Beginnings Program (NBP), a preventive parenting intervention, led to changes in coping strategies and coping efficacy in emerging adults whose families had participated in the program 15 years earlier. Gender and baseline risk were examined as moderators of these relations. Participants (M = 25.6 years; 50% female) were from 240 families that had participated in an experimental trial (NBP [mother-only, mother-child] vs. literature control). Data from the pretest and 15-year follow-up were used. Multiple regression analyses revealed that pretest risk interacted with program participation in the mother-only condition of the NBP such that offspring entering the program with higher pretest risk reported significantly less avoidant coping 15 years later. There was a marginal effect of participation in the NBP on problem-focused coping; emerging adults who had participated in the NBP had marginally higher levels of problem-focused coping. There were no significant main effects nor interactive program by risk or program by gender effects on support coping or coping efficacy. Results are discussed in terms of their implications for implementation of preventive interventions and research on pathways of coping.
ContributorsRhodes, Charla Aubrey (Author) / Wolchik, Sharlene A (Thesis advisor) / Tein, Jenn-Yun (Committee member) / Leucken, Linda (Committee member) / Arizona State University (Publisher)
Created2019