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- Genre: Masters Thesis
Description
The moderating effects of five characteristics of peers--their effortful control, anger, sadness, aggression, and positive peer behavior--were investigated in two separate series of analyses of preschooler's social behavior: (a) the relation between children's own effortful control and social behavior, and (b) the relation between children's shyness and reticent behavior. Latent variable interactions were conducted in a structural equation framework. Peer context anger and effortful control, albeit with unexpected results, interacted with children's own characteristics to predict their behavior in both the EC and shy model series; these were the only significant interactions obtained for the EC model series. The relation between shyness and reticent behavior, however, showed the greatest impact of peer context and, conversely, the greatest susceptibility to environmental variations; significant interactions were obtained in all five models, despite the limited range of peer context sadness and aggression observed in this study.
ContributorsHuerta, Snježana (Author) / Eisenberg, Nancy (Thesis advisor) / Spinrad, Tracy (Committee member) / Pina, Armando (Committee member) / Geiser, Christian (Committee member) / Arizona State University (Publisher)
Created2012
Description
Researchers are often interested in estimating interactions in multilevel models, but many researchers assume that the same procedures and interpretations for interactions in single-level models apply to multilevel models. However, estimating interactions in multilevel models is much more complex than in single-level models. Because uncentered (RAS) or grand mean centered (CGM) level-1 predictors in two-level models contain two sources of variability (i.e., within-cluster variability and between-cluster variability), interactions involving RAS or CGM level-1 predictors also contain more than one source of variability. In this Master’s thesis, I use simulations to demonstrate that ignoring the four sources of variability in a total level-1 interaction effect can lead to erroneous conclusions. I explain how to parse a total level-1 interaction effect into four specific interaction effects, derive equivalencies between CGM and centering within context (CWC) for this model, and describe how the interpretations of the fixed effects change under CGM and CWC. Finally, I provide an empirical example using diary data collected from working adults with chronic pain.
ContributorsMazza, Gina L (Author) / Enders, Craig K. (Thesis advisor) / Aiken, Leona S. (Thesis advisor) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2015
Description
For this thesis a Monte Carlo simulation was conducted to investigate the robustness of three latent interaction modeling approaches (constrained product indicator, generalized appended product indicator (GAPI), and latent moderated structural equations (LMS)) under high degrees of nonnormality of the exogenous indicators, which have not been investigated in previous literature. Results showed that the constrained product indicator and LMS approaches yielded biased estimates of the interaction effect when the exogenous indicators were highly nonnormal. When the violation of nonnormality was not severe (symmetric with excess kurtosis < 1), the LMS approach with ML estimation yielded the most precise latent interaction effect estimates. The LMS approach with ML estimation also had the highest statistical power among the three approaches, given that the actual Type-I error rates of the Wald and likelihood ratio test of interaction effect were acceptable. In highly nonnormal conditions, only the GAPI approach with ML estimation yielded unbiased latent interaction effect estimates, with an acceptable actual Type-I error rate of both the Wald test and likelihood ratio test of interaction effect. No support for the use of the Satorra-Bentler or Yuan-Bentler ML corrections was found across all three methods.
ContributorsCham, Hei Ning (Author) / West, Stephen G. (Thesis advisor) / Aiken, Leona S. (Committee member) / Enders, Craig K. (Committee member) / Arizona State University (Publisher)
Created2010
Description
The present study applied latent class analysis to a family-centered prevention
trial in early childhood to identify subgroups of families with differential responsiveness to the Family Check-up (FCU) intervention. The sample included 731 families of 2-year- olds randomized to the FCU or control and followed through age five with yearly follow up assessments (Dishion et al., 2014; Shaw et al., 2015). A two-step mixture model was used to examine whether specific constellations of family characteristics at age 2 (baseline) were related to intervention response at age 3, 4, and 5. The first step empirically identified latent classes of families based on a variety of demographic and adjustment variables selected on the basis of previous research on predictors of response to the FCU and parent training in general, as well as on the clinical observations of FCU implementers. The second step modeled the effect of the FCU on longitudinal change in children's problem behavior in each of the empirically derived latent classes. Results suggested a five-class solution, where a significant intervention effect of moderate-to- large size was observed in one of the five classes. The families within the responsive class were characterized by child neglect, legal problems, and mental health issues. Pairwise comparisons revealed that the intervention effect was significantly greater in this class of families than in two other classes that were generally less at risk for the development of disruptive behavior problems, and post hoc analyses partially supported these results. Thus, results indicated that the FCU was most successful in reducing child problem behavior in the highly distressed group of families. We conclude by discussing the potential practical utility of these results and emphasizing the need for future research to evaluate this approach's predictive accuracy.
trial in early childhood to identify subgroups of families with differential responsiveness to the Family Check-up (FCU) intervention. The sample included 731 families of 2-year- olds randomized to the FCU or control and followed through age five with yearly follow up assessments (Dishion et al., 2014; Shaw et al., 2015). A two-step mixture model was used to examine whether specific constellations of family characteristics at age 2 (baseline) were related to intervention response at age 3, 4, and 5. The first step empirically identified latent classes of families based on a variety of demographic and adjustment variables selected on the basis of previous research on predictors of response to the FCU and parent training in general, as well as on the clinical observations of FCU implementers. The second step modeled the effect of the FCU on longitudinal change in children's problem behavior in each of the empirically derived latent classes. Results suggested a five-class solution, where a significant intervention effect of moderate-to- large size was observed in one of the five classes. The families within the responsive class were characterized by child neglect, legal problems, and mental health issues. Pairwise comparisons revealed that the intervention effect was significantly greater in this class of families than in two other classes that were generally less at risk for the development of disruptive behavior problems, and post hoc analyses partially supported these results. Thus, results indicated that the FCU was most successful in reducing child problem behavior in the highly distressed group of families. We conclude by discussing the potential practical utility of these results and emphasizing the need for future research to evaluate this approach's predictive accuracy.
ContributorsPelham, William (Author) / Dishion, Thomas J (Thesis advisor) / Tein, Jenn-Yun (Committee member) / Crnic, Keith A (Committee member) / Arizona State University (Publisher)
Created2016