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- All Subjects: Quantitative Psychology and Psychometrics
- All Subjects: Clinical Psychology
- Creators: Millsap, Roger
- Member of: ASU Electronic Theses and Dissertations
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
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
The purpose of this dissertation was to develop a Compassionate Communication Scale (CCS) by conducting a series of studies. The first study used qualitative data to identify and develop initial scale items. A series of follow-up studies used exploratory factor analysis to investigate the underlying structure of the CCS. A three-factor structure emerged, which included: Compassionate conversation, such as listening, letting the distressed person disclose feelings, and making empathetic remarks; compassionate touch, such as holding someone's hand or patting someone's back; and compassionate messaging, such as posting an encouraging message on a social networking site or sending a sympathetic email. The next study tested convergent and divergent validity by determining how the three forms of compassionate communication associate with various traits. Compassionate conversation was positively related to compassion, empathetic concern, perspective taking, emotional intelligence, social expressivity, emotional expressivity and benevolence, and negatively related to verbal aggressiveness and narcissism. Compassionate touch was positively correlated with compassion, empathetic concern, perspective taking, emotional intelligence, social expressivity, emotional expressivity, and benevolence, and uncorrelated with verbal aggressiveness and benevolence. Finally, compassionate messaging was positively correlated with social expressivity, emotional expressivity, and uncorrelated with verbal aggressiveness and narcissism. The next study focused on cross-validation and criterion-related validity. Correlations showing that self-reports of a person's compassionate communication were positively related to a friend or romantic partner's report of that person's compassionate communication provided cross-validation. The test for criterion-related validity examined whether compassionate communication predicts relational satisfaction. Regression analyses revealed that people were more relationally satisfied when they perceived themselves to use compassionate conversation, when they perceived their partner to use compassionate conversation, and when their partner reported using compassionate conversation. This finding did not extend to compassionate touch or compassionate messaging. In fact, in one regression analysis, people reported more relational satisfaction when they perceived that their partners used high levels of compassionate conversation and low levels of compassionate touch. Overall, the analyses suggest that of the three forms of compassionate communication, compassionate conversation is most strongly related to relational satisfaction. Taken together, this series of studies provides initial evidence for the validity of the CCS.
ContributorsRamos Salazar, Leslie (Author) / Guerrero, Laura (Thesis advisor) / Roberto, Anthony (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2013
Description
Despite the compelling nature of goodness of fit and widespread recognition of the concept, empirical support has lagged, potentially due to complexities inherent in measuring such a complicated, relational construct. The present study examined two approaches to measuring goodness of fit in mother-child dyads and prospectively explored associations to mother-child relationship quality, child behavior problems, and parenting stress across the preschool period. In addition, as goodness of fit might be particularly important for children with developmental delays, child developmental risk status was considered as a moderator of goodness of fit processes. Children with (n = 110) and without (n = 137) developmental delays and their mothers were coded while interacting during a number of lab tasks at child age 36 months and during naturalistic home observations at child age 48 months. Mothers and father completed questionnaires at child ages 36 and 60 months assessing child temperamental characteristics, child behavior problems, and parenting stress. Results highlight child-directed effects on mother-child goodness of fit processes across the early child developmental period. Although there was some evidence that mother-child goodness of fit was associated with parenting stress 2 years later, goodness of fit remains an elusive concept. More precise models and expanded developmental perspectives are needed in order to fully capture the transactional and dynamic nature of goodness of fit in the parent-child relationship.
ContributorsNewland, Rebecca Pauline (Author) / Crnic, Keith (Thesis advisor) / Bradley, Robert (Committee member) / Jahromi, Laudan (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2014
Description
The effects of preventive interventions are found to be related to participants' responsiveness to the program, or the degree to which participants attend sessions, engage in the material, and use the program skills. The current study proposes a multi-dimensional method for measuring responsiveness to the Family Bereavement Program (FBP), a parenting-focused program to prevent mental health problems for children who experienced the death of a parent. It examines the relations between individual-level risk-factors and responsiveness to the program, as well as the relations between responsiveness and program outcomes. The sample consists of 90 caregivers and 135 children assigned to the intervention condition of an efficacy trial of the FBP. Caregivers' responsiveness to the 12-week program was measured using a number of indicators, including attendance, completion of weekly "homework" assignments, overall program skill use, perceived helpfulness of the program and program skills, and perceived group environment. Three underlying dimensions of responsiveness were identified: Skill Use, Program Liking, and Perceived Group Environment. Positive parenting and child externalizing problems at baseline were found to predict caregiver Skill Use. Skill Use and Perceived Group Environment predicted changes in caregiver grief and reports of child behavior problems at posttest and 11-month follow-up. Caregivers with better Skill Use had better positive parenting outcomes. Skill use mediated the relation between baseline positive parenting and improvements in positive parenting at 11-month follow-up.
ContributorsSchoenfelder, Erin (Author) / Sandler, Irwin N. (Thesis advisor) / Wolchik, Sharlene (Committee member) / Millsap, Roger (Committee member) / Barrera, Manuel (Committee member) / Arizona State University (Publisher)
Created2012
Description
The purpose of this study was to investigate the effect of complex structure on dimensionality assessment in compensatory and noncompensatory multidimensional item response models (MIRT) of assessment data using dimensionality assessment procedures based on conditional covariances (i.e., DETECT) and a factor analytical approach (i.e., NOHARM). The DETECT-based methods typically outperformed the NOHARM-based methods in both two- (2D) and three-dimensional (3D) compensatory MIRT conditions. The DETECT-based methods yielded high proportion correct, especially when correlations were .60 or smaller, data exhibited 30% or less complexity, and larger sample size. As the complexity increased and the sample size decreased, the performance typically diminished. As the complexity increased, it also became more difficult to label the resulting sets of items from DETECT in terms of the dimensions. DETECT was consistent in classification of simple items, but less consistent in classification of complex items. Out of the three NOHARM-based methods, χ2G/D and ALR generally outperformed RMSR. χ2G/D was more accurate when N = 500 and complexity levels were 30% or lower. As the number of items increased, ALR performance improved at correlation of .60 and 30% or less complexity. When the data followed a noncompensatory MIRT model, the NOHARM-based methods, specifically χ2G/D and ALR, were the most accurate of all five methods. The marginal proportions for labeling sets of items as dimension-like were typically low, suggesting that the methods generally failed to label two (three) sets of items as dimension-like in 2D (3D) noncompensatory situations. The DETECT-based methods were more consistent in classifying simple items across complexity levels, sample sizes, and correlations. However, as complexity and correlation levels increased the classification rates for all methods decreased. In most conditions, the DETECT-based methods classified complex items equally or more consistent than the NOHARM-based methods. In particular, as complexity, the number of items, and the true dimensionality increased, the DETECT-based methods were notably more consistent than any NOHARM-based method. Despite DETECT's consistency, when data follow a noncompensatory MIRT model, the NOHARM-based method should be preferred over the DETECT-based methods to assess dimensionality due to poor performance of DETECT in identifying the true dimensionality.
ContributorsSvetina, Dubravka (Author) / Levy, Roy (Thesis advisor) / Gorin, Joanna S. (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2011
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
Item response theory (IRT) and related latent variable models represent modern psychometric theory, the successor to classical test theory in psychological assessment. While IRT has become prevalent in the assessment of ability and achievement, it has not been widely embraced by clinical psychologists. This appears due, in part, to psychometrists' use of unidimensional models despite evidence that psychiatric disorders are inherently multidimensional. The construct validity of unidimensional and multidimensional latent variable models was compared to evaluate the utility of modern psychometric theory in clinical assessment. Archival data consisting of 688 outpatients' presenting concerns, psychiatric diagnoses, and item level responses to the Brief Symptom Inventory (BSI) were extracted from files at a university mental health clinic. Confirmatory factor analyses revealed that models with oblique factors and/or item cross-loadings better represented the internal structure of the BSI in comparison to a strictly unidimensional model. The models were generally equivalent in their ability to account for variance in criterion-related validity variables; however, bifactor models demonstrated superior validity in differentiating between mood and anxiety disorder diagnoses. Multidimensional IRT analyses showed that the orthogonal bifactor model partitioned distinct, clinically relevant sources of item variance. Similar results were also achieved through multivariate prediction with an oblique simple structure model. Receiver operating characteristic curves confirmed improved sensitivity and specificity through multidimensional models of psychopathology. Clinical researchers are encouraged to consider these and other comprehensive models of psychological distress.
ContributorsThomas, Michael Lee (Author) / Lanyon, Richard (Thesis advisor) / Barrera, Manuel (Committee member) / Levy, Roy (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2011
Children's coping efforts and coping efficacy: effects of parenting, surgency, and effortful control
Description
Stress responses play a central role in the development of psychopathology. Coping efforts, one subset of stress responses, have been shown to influence the relations between stress and adjustment. Although the relations between youths' coping and emotional and behavioral outcomes are well-documented, less is known about the factors that predict youths' coping. Given their importance for adaptation, understanding influences on youths' coping has important implications for developmental theories and preventive interventions. The current study examined the main and interactive effects of positive parenting and youths' temperament on youths' coping efforts and coping efficacy one year later in a sample of 192 youth aged 9-15 years when assessed initially. Data used were from the first and third waves of a four-wave, prospective, longitudinal study of families where one or both parents recently became unemployed. Positive parenting was measured with a combination of mother-report, child-report, and observational measures. Temperament was assessed with mother-report, child-report, and/or teacher-report measures. Children reported on their coping. It was hypothesized that positive parenting, effortful control, and surgency would be positively associated with active coping and coping efficacy, and negatively associated with avoidant coping. Further, it was hypothesized that the relations between positive parenting and youths' coping would be stronger for youths low in effortful control or surgency. Structural equation modeling with latent variables revealed no significant main effects of positive parenting, effortful control, or surgency on youths' coping efforts or coping efficacy. Path analyses revealed no significant positive parenting by temperament interactions in the prediction of youths' coping efforts or coping efficacy. Several significant correlations between measures of positive parenting or surgency and youths' coping emerged. The pattern of correlations provided some support for the hypothesized relations. For example, aspects of positive parenting (e.g., maternal acceptance) and youth surgency were associated with more adaptive coping both concurrently and longitudinally, whereas an aspect of negative parenting (i.e., maternal rejection) was associated with less adaptive coping both concurrently and over time. Potential explanations of the unexpected findings and future directions for understanding the role of parenting and youths' temperament in youths' coping efforts and coping efficacy are discussed.
ContributorsVélez, Clorinda Eileen (Author) / Wolchik, Sharlene (Thesis advisor) / Eisenberg, Nancy (Thesis advisor) / Ayers, Tim (Committee member) / Millsap, Roger (Committee member) / Sandler, Irwin (Committee member) / Arizona State University (Publisher)
Created2010
Description
The purpose of this thesis study was to evaluate the nature of social anxiety in clinic-referred African American children versus their Caucasian counterparts. In particular, social anxiety symptom endorsement along the Social Phobia and Anxiety Inventory Scale for Children (SPAI-C; Beidel, Turner, & Morris, 1995) was examined in a sample of 107 African American and 364 Caucasian children (ages 7- to 17-years old) referred for anxiety. To evaluate symptom endorsement, simple descriptive analyses were conducted whereas measurement invariance tests were examined using confirmatory factor analyses. For the most commonly endorsed items, African American and Caucasian children shared seven of the top 10 most commonly identified social anxiety symptoms. Similar social fears across ethnicity focused on "assertiveness in situations perceived to be difficult" and ""speaking to large groups of peers they do not know." Findings also showed that African American children were more likely to report symptoms of "shaking when in social situations" than Caucasian children, and Caucasian children were more likely to report symptoms of "embarrassment when in front of adults" compared to African American children, but this was also on the basis of two items. When it came to the five factors of the SPAI-C, results showed measurement invariance across African American and Caucasian children. Overall, there were more similarities than differences between African American and Caucasian children in social anxiety symptoms based on the SPAI-C. Findings from this thesis study shed light on how to best accurately identify social anxiety among African American children compared to Caucasians, a contribution that can potentially impact assessment, treatment planning, and program response evaluation.
ContributorsWynne, Henry (Author) / Pina, Armando (Thesis advisor) / Gonzales, Nancy (Committee member) / Millsap, Roger (Committee member) / Arizona State University (Publisher)
Created2013