Matching Items (31)
151719-Thumbnail Image.png
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

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
151957-Thumbnail Image.png
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

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
151501-Thumbnail Image.png
Description
Daily dairies and other intensive measurement methods are increasingly used to study the relationships between two time varying variables X and Y. These data are commonly analyzed using longitudinal multilevel or bivariate growth curve models that allow for random effects of intercept (and sometimes also slope) but which do not

Daily dairies and other intensive measurement methods are increasingly used to study the relationships between two time varying variables X and Y. These data are commonly analyzed using longitudinal multilevel or bivariate growth curve models that allow for random effects of intercept (and sometimes also slope) but which do not address the effects of weekly cycles in the data. Three Monte Carlo studies investigated the impact of omitting the weekly cycles in daily dairy data under the multilevel model framework. In cases where cycles existed in both the time-varying predictor series (X) and the time-varying outcome series (Y) but were ignored, the effects of the within- and between-person components of X on Y tended to be biased, as were their corresponding standard errors. The direction and magnitude of the bias depended on the phase difference between the cycles in the two series. In cases where cycles existed in only one series but were ignored, the standard errors of the regression coefficients for the within- and between-person components of X tended to be biased, and the direction and magnitude of bias depended on which series contained cyclical components.
ContributorsLiu, Yu (Author) / West, Stephen G. (Thesis advisor) / Enders, Craig K. (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2013
152444-Thumbnail Image.png
Description
The present study examined the association of pain intensity and goal progress in a community sample of 132 adults with chronic pain who participated in a 21 day diary study. Multilevel modeling was employed to investigate the effect of morning pain intensity on evening goal progress as mediated by pain's

The present study examined the association of pain intensity and goal progress in a community sample of 132 adults with chronic pain who participated in a 21 day diary study. Multilevel modeling was employed to investigate the effect of morning pain intensity on evening goal progress as mediated by pain's interference with afternoon goal pursuit. Moderation effects of pain acceptance and pain catastrophizing on the associations between pain and interference with both work and lifestyle goal pursuit were also tested. The results showed that the relationship between morning pain and pain's interference with work goal pursuit in the afternoon was significantly moderated by a pain acceptance. In addition, it was found that the mediated effect differed across levels of pain acceptance; that is: (1) there was a significant mediation effect when pain acceptance was at its mean and one standard deviation below the mean; but (2) there was no mediation effect when pain acceptance was one standard deviation above the mean. It appears that high pain acceptance significantly attenuates the power of nociception in disrupting one's work goal pursuit. However, in the lifestyle goal model, none of the moderators were significant nor was there a significant association between pain interference with goal pursuit and goal progress. Only morning pain intensity significantly predicted afternoon interference with lifestyle goal pursuit. Further interpretation of the present findings and potential explanations of those inconsistencies are elaborated on discussion. Limitations and the clinical implication of the current study were considered, along with suggestions for future studies.
ContributorsMun, Chung Jung (Author) / Karoly, Paul (Thesis advisor) / Okun, Morris A. (Committee member) / Enders, Craig K. (Committee member) / Arizona State University (Publisher)
Created2014
152883-Thumbnail Image.png
Description
The primary aim of this study was to investigate resilient profiles in low-income Mexican American (MA) mothers. MA mothers are part of an under researched population, the fastest growing ethnic minority group, and have the highest birth rate in the United States, presenting a significant public health concern. The

The primary aim of this study was to investigate resilient profiles in low-income Mexican American (MA) mothers. MA mothers are part of an under researched population, the fastest growing ethnic minority group, and have the highest birth rate in the United States, presenting a significant public health concern. The transition to motherhood can be an emotionally and physically complex time for women, particularly in the context of a stressful low-income environment. Although most low-income women navigate this transition well, a significant number of mothers develop moderate to severe depressive symptoms. The proposed research investigated profiles of resilience during the prenatal period using a person-centered approach via latent profile analysis. In alignment with current resilience theories, several domains of resilience were investigated including psychological, social, and cultural adherence (e.g., maintaining specific cultural traditions). Concurrent prenatal depressive symptoms and stress were correlated with the profiles in order to establish validity. Six week postpartum depressive symptoms and physiological processes (e.g., overall cortisol output, heart rate variability, and sleep) were also predicted by the prenatal resilient profiles. The resulting data revealed three separate profiles: low-resource, high-resource Anglo, and high-resource Mexican. These resilience profiles had differential associations with concurrent depressive symptoms and stress, such that women in the high-resource profiles reported less depressive symptoms and stress prenatally. Further, profile differences regarding cortisol output, resting heart rate variability, were also found, but there were no differences in insomnia symptoms. Profile classification also moderated the effects of prenatal economic stress on postpartum depressive symptoms, such that women in the high-resource Mexican profile were at risk for higher postpartum depressive symptoms under high economic stress compared to the high-resource Anglo group, which demonstrated a more resilient response. Overall, the results suggest the presence of multiple clusters of prenatal resilience within a sample of MA mothers facing health disparities, with various effects on perinatal mental health and postpartum physiological processes. The results also highlight the need for multi-dimensional models of resilience and the possible implications for interventions.
ContributorsGress Smith, Jenna L (Author) / Luecken, Linda J. (Thesis advisor) / Gonzales, Nancy (Committee member) / Okun, Morris (Committee member) / Zautra, Alex (Committee member) / Arizona State University (Publisher)
Created2014
152979-Thumbnail Image.png
Description
Research demonstrating the importance of the paternal role has been largely conducted using samples of Caucasian men, leaving a gap in what is known about fathering in minority cultures. Family systems theories highlight the dynamic interrelations between familial roles and relationships, and suggest that comprehensive studies of fathering require attention

Research demonstrating the importance of the paternal role has been largely conducted using samples of Caucasian men, leaving a gap in what is known about fathering in minority cultures. Family systems theories highlight the dynamic interrelations between familial roles and relationships, and suggest that comprehensive studies of fathering require attention to the broad family and cultural context. During the early infancy period, mothers' and fathers' postpartum adjustment may represent a critical source of influence on father involvement. For the current study, Mexican American (MA) women (N = 125) and a subset of their romantic partners/biological fathers (N = 57) reported on their depressive symptoms and levels of father involvement (paternal engagement, accessibility, and responsibility) during the postpartum period. Descriptive analyses suggested that fathers are involved in meaningful levels of care during infancy. Greater paternal postpartum depression (PPD) was associated with lower levels of father involvement. Maternal PPD interacted with paternal gender role attitudes to predict father involvement. At higher levels of maternal PPD, involvement increased among fathers adhering to less segregated gender role attitudes and decreased among fathers who endorsed more segregated gender role attitudes. Within select models, differences in the relations were observed between mothers' and fathers' reports of paternal involvement. Results bring attention to the importance of examining contextual influences on early fathering in MA families and highlight the unique information that may be gathered from separate maternal and paternal reports of father involvement.
ContributorsRoubinov, Danielle S (Author) / Luecken, Linda J. (Thesis advisor) / Crnic, Keith A (Committee member) / Enders, Craig K. (Committee member) / Gonzales, Nancy A. (Committee member) / Arizona State University (Publisher)
Created2014
153523-Thumbnail Image.png
Description
Low-income Mexican American women face significant risk for poor health during the postpartum period. Chronic stressors are theorized to negatively impact mental and physical health outcomes. However, physiological factors associated with increased self-regulatory capacity, such as resting heart rate variability, may buffer the impact of stress. In a sample of

Low-income Mexican American women face significant risk for poor health during the postpartum period. Chronic stressors are theorized to negatively impact mental and physical health outcomes. However, physiological factors associated with increased self-regulatory capacity, such as resting heart rate variability, may buffer the impact of stress. In a sample of 322 low-income Mexican American women (mother age 18-42; 84% Spanish-speaking; modal family income $10,000-$15,000), the interactive influence of resting heart rate variability and three chronic prenatal stressors (daily hassles, negative life events, economic stress) on maternal cortisol output, depressive symptoms, and self-rated health at 12 weeks postpartum was assessed. The hypothesized interactive effects between resting heart rate variability and the chronic prenatal stressors on the health outcomes were not supported by the data. However, results showed that a higher number of prenatal daily hassles was associated with increased postpartum depressive symptoms, and a higher number of prenatal negative life events was associated with lower postpartum cortisol output. These results suggest that elevated chronic stress during the prenatal period may increase risk for poor health during the postpartum period.
ContributorsJewell, Shannon Linda (Author) / Luecken, Linda J. (Thesis advisor) / Lemery-Chalfant, Kathryn (Committee member) / Perez, Marisol (Committee member) / Arizona State University (Publisher)
Created2015
153052-Thumbnail Image.png
Description
Postpartum depression (PPD) is a significant public health concern affecting up to half a million U.S. women annually. Mexican-American women experience substantially higher rates of PPD, and represent an underserved population with significant health disparities that put these women and their infants at greater risk for substantial psychological and developmental

Postpartum depression (PPD) is a significant public health concern affecting up to half a million U.S. women annually. Mexican-American women experience substantially higher rates of PPD, and represent an underserved population with significant health disparities that put these women and their infants at greater risk for substantial psychological and developmental difficulties. The current study utilized data on perceived stress, depression, maternal parenting behavior, and infant social-emotional and cognitive development from 214 Mexican-American mother-infant dyads. The first analysis approach utilized a latent intercept (LI) model to examine how overall mean levels and within-person deviations of perceived stress, depressive symptoms, and maternal parenting behavior are related across the postpartum period. Results indicated large, positive between- and within-person correlations between perceived stress and depression. Neither perceived stress nor depressive symptoms were found to have significant between- or within-person associations with the parenting variables. The second analysis approach utilized an autoregressive cross-lagged model with tests of mediation to identify underlying mechanisms among perceived stress, postpartum depressive symptoms, and maternal parenting behavior in the prediction of infant social-emotional and cognitive development. Results indicated that increased depressive symptoms at 12- and 18-weeks were associated with subsequent reports of increased perceived stress at 18- and 24-weeks, respectively. Perceived stress at 12-weeks was found to be negatively associated with subsequent non-hostility at 18-weeks, and both sensitivity and non-hostility were found to be associated with infant cognitive development and social-emotional competencies at 12 months of age (52-weeks), but not with social-emotional problems. The results of the mediation analyses showed that non-hostility at 18- and 24-weeks significantly mediated the association between perceived stress at 12-weeks and infant cognitive development and social-emotional competencies at 52-weeks. The findings extend research that sensitive parenting in early childhood is as important to the development of cognitive ability, social behavior, and emotion regulation in ethnic minority cultures as it is in majority culture families; that maternal perceptions of stress may spillover into parenting behavior, resulting in increased hostility and negatively influencing infant cognitive and social-emotional development; and that symptoms of depressed mood may influence the experience of stress.
ContributorsCiciolla, Lucia (Author) / Crnic, Keith A (Thesis advisor) / West, Stephen G. (Thesis advisor) / Luecken, Linda J. (Committee member) / Presson, Clark C. (Committee member) / Arizona State University (Publisher)
Created2014
153391-Thumbnail Image.png
Description
Missing data are common in psychology research and can lead to bias and reduced power if not properly handled. Multiple imputation is a state-of-the-art missing data method recommended by methodologists. Multiple imputation methods can generally be divided into two broad categories: joint model (JM) imputation and fully conditional specification (FCS)

Missing data are common in psychology research and can lead to bias and reduced power if not properly handled. Multiple imputation is a state-of-the-art missing data method recommended by methodologists. Multiple imputation methods can generally be divided into two broad categories: joint model (JM) imputation and fully conditional specification (FCS) imputation. JM draws missing values simultaneously for all incomplete variables using a multivariate distribution (e.g., multivariate normal). FCS, on the other hand, imputes variables one at a time, drawing missing values from a series of univariate distributions. In the single-level context, these two approaches have been shown to be equivalent with multivariate normal data. However, less is known about the similarities and differences of these two approaches with multilevel data, and the methodological literature provides no insight into the situations under which the approaches would produce identical results. This document examined five multilevel multiple imputation approaches (three JM methods and two FCS methods) that have been proposed in the literature. An analytic section shows that only two of the methods (one JM method and one FCS method) used imputation models equivalent to a two-level joint population model that contained random intercepts and different associations across levels. The other three methods employed imputation models that differed from the population model primarily in their ability to preserve distinct level-1 and level-2 covariances. I verified the analytic work with computer simulations, and the simulation results also showed that imputation models that failed to preserve level-specific covariances produced biased estimates. The studies also highlighted conditions that exacerbated the amount of bias produced (e.g., bias was greater for conditions with small cluster sizes). The analytic work and simulations lead to a number of practical recommendations for researchers.
ContributorsMistler, Stephen (Author) / Enders, Craig K. (Thesis advisor) / Aiken, Leona (Committee member) / Levy, Roy (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2015
153393-Thumbnail Image.png
Description
Daily life stressors and negative emotional experiences predict poor physical and psychological health. The stress response of the hypothalamic-pituitary-adrenal axis is a primary biological system through which stressful experiences impact health and well-being across development. Individuals differ in their capacity for self-regulation and utilize various coping strategies in response to

Daily life stressors and negative emotional experiences predict poor physical and psychological health. The stress response of the hypothalamic-pituitary-adrenal axis is a primary biological system through which stressful experiences impact health and well-being across development. Individuals differ in their capacity for self-regulation and utilize various coping strategies in response to stress. Everyday experiences and emotions are highly variable during adolescence, a time during which self-regulatory abilities may become particularly important for adapting to shifting social contexts. Many adolescents in the U.S. enter college after high school, a context characterized by new opportunities and challenges for self-regulation. Guided by biopsychosocial and daily process approaches, the current study explored everyday stress and negative affect (NA), cortisol reactivity, and self-regulation assessed at the momentary, daily, and trait level among a racially/ethnically and socioeconomically diverse sample of first-year college students (N = 71; Mage = 18.85; 23% male; 52% non-Hispanic White) who completed a modified ecological momentary assessment. It was expected that within-person increases in momentary stress level or NA would be associated with cortisol reactivity assessed in college students' naturalistic settings. It was predicted that these within-person associations would differ based on engagement coping responses assessed via momentary diary reports, by the range of engagement coping responses assessed via diary reports at the end of the day, and by higher trait levels of self-regulation assessed via standard self-report questionnaire. Within-person increases in momentary stress level were significantly associated with momentary elevations in cortisol only during moments characterized by greater than usual engagement coping efforts (i.e., within-person

increases). At a different level of analysis, within-person increases in momentary stress level were significantly associated with increases in cortisol only for those with low trait levels of coping efficacy and engagement coping. On average, within-person increases in momentary NA were significantly associated with cortisol reactivity. Tests of moderation revealed this momentary association was only significant for those with low trait levels of support-seeking coping.
ContributorsSladek, Michael Ronald (Author) / Doane, Leah D (Thesis advisor) / Eisenberg, Nancy (Committee member) / Luecken, Linda J. (Committee member) / Arizona State University (Publisher)
Created2015