Matching Items (34)
Description
In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required in contrast to second order models that include the measurement and the structural relationships among the variables. However, the use of composites assumes that longitudinal measurement invariance holds; that is, it is assumed that that the relationships among the items and the latent variables remain constant over time. Previous studies conducted on latent growth models (LGM) have shown that when longitudinal metric invariance is violated, the parameter estimates are biased and that mistaken conclusions about growth can be made. The purpose of the current study was to examine the impact of non-invariant loadings and non-invariant intercepts on two longitudinal models: the LGM and the autoregressive quasi-simplex model (AR quasi-simplex). A second purpose was to determine if there are conditions in which researchers can reach adequate conclusions about stability and growth even in the presence of violations of invariance. A Monte Carlo simulation study was conducted to achieve the purposes. The method consisted of generating items under a linear curve of factors model (COFM) or under the AR quasi-simplex. Composites of the items were formed at each time point and analyzed with a linear LGM or an AR quasi-simplex model. The results showed that AR quasi-simplex model yielded biased path coefficients only in the conditions with large violations of invariance. The fit of the AR quasi-simplex was not affected by violations of invariance. In general, the growth parameter estimates of the LGM were biased under violations of invariance. Further, in the presence of non-invariant loadings the rejection rates of the hypothesis of linear growth increased as the proportion of non-invariant items and as the magnitude of violations of invariance increased. A discussion of the results and limitations of the study are provided as well as general recommendations.
ContributorsOlivera-Aguilar, Margarita (Author) / Millsap, Roger E. (Thesis advisor) / Levy, Roy (Committee member) / MacKinnon, David (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2013
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 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
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
Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not in statistical analyses. Bayesian methods incorporate prior knowledge into the statistical analysis in the form of a prior distribution. When prior information about a relationship is available, the estimates obtained could differ drastically depending on the choice of Bayesian or frequentist method. Study 1 in this project compared the performance of five methods for obtaining interval estimates of the mediated effect in terms of coverage, Type I error rate, empirical power, interval imbalance, and interval width at N = 20, 40, 60, 100 and 500. In Study 1, Bayesian methods with informative prior distributions performed almost identically to Bayesian methods with diffuse prior distributions, and had more power than normal theory confidence limits, lower Type I error rates than the percentile bootstrap, and coverage, interval width, and imbalance comparable to normal theory, percentile bootstrap, and the bias-corrected bootstrap confidence limits. Study 2 evaluated if a Bayesian method with true parameter values as prior information outperforms the other methods. The findings indicate that with true values of parameters as the prior information, Bayesian credibility intervals with informative prior distributions have more power, less imbalance, and narrower intervals than Bayesian credibility intervals with diffuse prior distributions, normal theory, percentile bootstrap, and bias-corrected bootstrap confidence limits. Study 3 examined how much power increases when increasing the precision of the prior distribution by a factor of ten for either the action or the conceptual path in mediation analysis. Power generally increases with increases in precision but there are many sample size and parameter value combinations where precision increases by a factor of 10 do not lead to substantial increases in power.
ContributorsMiocevic, Milica (Author) / Mackinnon, David P. (Thesis advisor) / Levy, Roy (Committee member) / West, Stephen G. (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2014
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 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
Description
Maternal intrusiveness is an important predictor of child mental health problems. Evidence links high levels of maternal intrusiveness to later infant negativity, and child internalizing problems. However, children also influence the manner in which parents interact with them. For example, infants that show more negative emotionality elicit less positive parenting in their caregivers. Infant affect is also associated with later child internalizing difficulties. Although previous research has demonstrated that maternal intrusiveness is related to infant affect and child internalizing symptomatology, and that infant affect is a predictor of internalizing problems and parenting, no studies have looked at the transactional relations between early maternal intrusiveness and infant affect, and whether these relations in infancy predict later childhood internalizing symptomatology. The present study investigates young children's risk for internalizing problems as a function of the interplay between maternal intrusiveness and infant affect during the early infancy period in a low-income, Mexican-American sample. Participants included 323 Mexican-American women and their infants. Data were collected when the infants were 12, 18, 24, and 52 weeks old. Mothers were asked to interact with their infants in semi-structured tasks, and mother and infant behaviors were coded at 12, 18, and 24 weeks. Maternal intrusiveness was globally rated, and duration of infant negative- and positive affect was recorded. Mother reports of child Internalizing symptomatology were obtained at 52 weeks. Findings suggest that there are transactional relations between early maternal intrusiveness and infant negative affect, while the relations between infant positive affect and maternal intrusiveness are unidirectional, in that infant positivity influences parenting but not vice versa. Further, findings also imply that neither maternal intrusiveness, nor infant affect, influence later toddler internalizing symptomatology. Identifying risk processes in a Mexican-American sample adds to our understanding of emerging infant difficulties in this population, and may have implications for early interventions.
ContributorsRystad, Ida A (Author) / Crnic, Keith A (Thesis advisor) / Enders, Craig (Committee member) / Bradley, Robert (Committee member) / Arizona State University (Publisher)
Created2014
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) 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
Description
Externalizing behaviors are pervasive, widespread, and disruptive across a multitude of settings and developmental contexts. While the conventional diathesis-stress model typically measures the disordered end of the spectrum, studies that span the range of behavior, from externalizing to competence behaviors, are necessary to see the full picture. To that end, this study examined the additive and nonadditive relations of a dimension of parenting (ranging from warm to rejecting), and variants in dopamine, vasopressin, and neuropeptide-y receptor genes on externalizing/competence in a large sample of predominantly Caucasian twin children in toddlerhood, middle childhood, and early adolescence. Variants within each gene were hypothesized to increase biological susceptibility to both negative and positive environments. Consistent with prediction, warmth related to lower externalizing/higher competence at all ages. Earlier levels of externalizing/competence washed out the effect of parental warmth on future externalizing/competence with the exception of father warmth in toddlerhood marginally predicting change in externalizing/competence from toddlerhood to middle childhood. Warmth was a significant moderator of the heritability of behavior in middle childhood and early adolescence such that behavior was less heritable (mother report) and more heritable (father report) in low warmth environments. Interactions with warmth and the dopamine and vasopressin genes in middle childhood and early adolescence emphasize the moderational role gene variants play in relations between the rearing environment and child behavior. For dopamine, the long variant related to increased sensitivity to parent warmth such that the children displayed more externalizing behaviors when exposed to rejection but they also displayed more competence behaviors when exposed to high warmth. Vasopressin moderation was only present under conditions of parental warmth, not rejection. Interactions with neuropeptide-y and warmth were not significant. The picture that emerges is one of gene-environment interplay, wherein the influence of both parenting and child genotype each depend on the level of the other. As genetic research moves forward, gene variants previously implicated as conferring risk for disorder should be reexamined in conjunction with salient aspects of the environment on the full range of the behavioral outcome of interest.
ContributorsO'Brien, T. Caitlin (Author) / Lemery-Chalfant, Kathryn (Thesis advisor) / Eisenberg, Nancy (Committee member) / Enders, Craig (Committee member) / Nagoshi, Craig (Committee member) / Arizona State University (Publisher)
Created2011
Description
Coarsely grouped counts or frequencies are commonly used in the behavioral sciences. Grouped count and grouped frequency (GCGF) that are used as outcome variables often violate the assumptions of linear regression as well as models designed for categorical outcomes; there is no analytic model that is designed specifically to accommodate GCGF outcomes. The purpose of this dissertation was to compare the statistical performance of four regression models (linear regression, Poisson regression, ordinal logistic regression, and beta regression) that can be used when the outcome is a GCGF variable. A simulation study was used to determine the power, type I error, and confidence interval (CI) coverage rates for these models under different conditions. Mean structure, variance structure, effect size, continuous or binary predictor, and sample size were included in the factorial design. Mean structures reflected either a linear relationship or an exponential relationship between the predictor and the outcome. Variance structures reflected homoscedastic (as in linear regression), heteroscedastic (monotonically increasing) or heteroscedastic (increasing then decreasing) variance. Small to medium, large, and very large effect sizes were examined. Sample sizes were 100, 200, 500, and 1000. Results of the simulation study showed that ordinal logistic regression produced type I error, statistical power, and CI coverage rates that were consistently within acceptable limits. Linear regression produced type I error and statistical power that were within acceptable limits, but CI coverage was too low for several conditions important to the analysis of counts and frequencies. Poisson regression and beta regression displayed inflated type I error, low statistical power, and low CI coverage rates for nearly all conditions. All models produced unbiased estimates of the regression coefficient. Based on the statistical performance of the four models, ordinal logistic regression seems to be the preferred method for analyzing GCGF outcomes. Linear regression also performed well, but CI coverage was too low for conditions with an exponential mean structure and/or heteroscedastic variance. Some aspects of model prediction, such as model fit, were not assessed here; more research is necessary to determine which statistical model best captures the unique properties of GCGF outcomes.
ContributorsCoxe, Stefany (Author) / Aiken, Leona S. (Thesis advisor) / West, Stephen G. (Thesis advisor) / Mackinnon, David P (Committee member) / Reiser, Mark R. (Committee member) / Arizona State University (Publisher)
Created2012
Description
Family adaptation to child developmental disability is a dynamic transactional process that has yet to be tested in a longitudinal, rigorous fashion. In addition, although children with developmental delays frequently have behavior problems, not enough research has examined possible underlying mechanisms in the relation between child developmental delay, adaptation and behavior problems. In the current study, factor analysis examined how best to conceptualize the construct of family adaptation to developmental delay. Also, longitudinal growth curve modeling tested models in which child behavior problems mediated the relation between developmental risk and indices of family adaptation. Participants included 130 typically developing children and their families (Mental Development Index [MDI] > 85) and 104 children with developmental delays and their families (MDI < 85). Data were collected yearly between the ages of three and eight as part of a multi-site, longitudinal investigation examining the interrelations among children's developmental status, family processes, and the emergence of child psychopathology. Results of the current study indicated that adaptation is best conceptualized as a multi-index construct. Different aspects of adaptation changed in unique ways over time, with some facets of adaptation remaining stable while others fluctuated. Child internalizing and externalizing behavior problems were found to decrease over time for both children with developmental delays and typically developing children. Child behavior problems were also found to mediate the relation between developmental risk and family adaptation for over half of the mediation pathways. Significant mediation results indicated that children with developmental delays showed higher early levels of behavior problems, which in turn was associated with more maladaptive adaptation. These findings provide further evidence that families of children with developmental delays experience both positive and more challenging changes in their families over time. This study implies important next steps for research and clinical practice in the area of developmental disability.
ContributorsPedersen y Arbona, Anita (Author) / Crnic, Keith A (Thesis advisor) / Sandler, Irwin (Committee member) / Lemery, Kathryn (Committee member) / Enders, Craig (Committee member) / Arizona State University (Publisher)
Created2011