Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the distributions of the factors are modeled nonparametrically through a dynamic hierarchical Dirichlet process prior. A Markov chain Monte Carlo algorithm is developed for fitting the model, and the methodology is exemplified through a study of the dynamics of public attitudes toward science and technology in the United States over the period 1992?C2001.     

Dimensions of Religion and Spirituality: A Longitudinal Topic Modeling Approach

In lieu of the traditional text data analysis methods, structural topic modeling was utilized to analyze the text contents of 255 self-report inventories of religion and spirituality (R/S) published from 1929 to 2017. The study had two objectives: (a) to clarify and identify the latent dimensions of R/S inherent in the items of the measures; and (b) to examine and demonstrate the usefulness of a longitudinal topic modeling in the study of R/S. We identified 5,617 unique text terms from the measures and fitted topic models on those terms to extract latent dimensions called topics. We also simultaneously analyzed the longitudinal effect of publication decade (i.e., 1950s–2010s) on the topics. A topic model with three topics was chosen to best support the data: Experience of Transcendence (Topic 1), Engagement in Transcendence (Topic 2), and Essence of Transcendence (Topic 3). In addition, the longitudinal analysis revealed that Topic 1 showed a continual increase over the decades, while Topics 2 and 3 both demonstrated a gradual decrease, in effect matching the general trend of Topic 1's increasing popularity in society and the academia.     

Adolescent Effortful Control as Moderator of Father's Psychological Control in Externalizing Problems: A Longitudinal Study

This longitudinal study investigates the moderating role of a temperamental trait, the effortful control, in the relation between father's psychological control and externalizing problems. In Wave 1, the participants included 507 adolescents attending the second classes of two public schools situated in two Italian cities; in Wave 2, 482 adolescents attending the fifth classes of high school participated again in the study. The results demonstrated a positive contribution of paternal achievement-oriented psychological control to externalizing problems and a moderator effect of effortful control in the relationship between the father's psychological control and externalizing problems. These findings extend current knowledge on the role of the father in the difficult task of balancing the promotion of individuality without falling into psychological control that can trigger externalizing problems among adolescents, especially when the temperament of the latter does not foresee the availability of self-regulating abilities that mediate disadvantageous reactivity.     

An Examination of a Functional Mixed-Effects Modeling Approach to the Analysis of Longitudinal Data

Growth curve modeling is one of the main analytical approaches to study change over time. Growth curve models are commonly estimated in the linear and nonlinear mixed-effects modeling framework in which both the mean and person-specific curves are modeled parametrically with functions of time such as the linear, quadratic, and exponential. However, when more complex nonlinear trajectories need to be estimated and researchers do not have a priori knowledge of an appropriate functional form of growth, parametric models may be too restrictive. This paper reviews functional mixed-effects models, a nonparametric extension of mixed-effects models that permit both the mean and person-specific curves to be estimated without assuming a prespecified functional form of growth. Details of the model are presented along with results from a simulation study and an empirical example. The simulation study showed functional mixed-effects models performed reasonably well under various conditions commonly associated with longitudinal panel data, such as few time points per person, irregularly spaced time points across persons, missingness, and nonlinear trajectories. The usefulness of functional mixed-effects models is illustrated by analyzing empirical data from the Early Childhood Longitudinal Study – Kindergarten Class of 1998–1999.     

Risk as a Moderator of the Effects of Prevention Programs for Children from Divorced Families: A Six-Year Longitudinal Study

Program by risk interactions were assessed to evaluate whether the long-term effects of two preventive interventions for children from divorced families were moderated by baseline levels of risk. Six-year prospective relations between childhood (ages 9-12) and adolescence (ages 15-19) were examined in 68 children who comprised the control group of a randomized trial. Analyses indicated that two childhood variables predicted multiple adolescent outcomes: environmental stressors and externalizing problems. A risk index composed of these 2 variables was highly predictive of internalizing and externalizing problems, competence, substance use, and mental disorder 6 years later. Analyses of the full sample (N = 218) indicated that program effects were greater for children with higher risk scores and that the programs attenuated the relation between risk and adolescent internalizing and externalizing problems, competence, and mental disorder.     

神经质人格调节青少年应激与抑郁症状的追踪研究

探讨神经质人格对青少年应激与抑郁症状的调节作用。采用自评的流调中心用抑郁量表、大五人格问卷-神经质分量表和青少年生活事件量表对618名在校高中生进行了首次测查,随后每隔3个月对被试的抑郁症状和生活事件进行追踪测查,追踪时间为期一年,结果发现:与低神经质青少年相比,随着生活事件应激水平的升高,高神经质青少年的抑郁躯体症状与心理症状增长速度更快。结论:神经质人格在青少年生活事件应激和抑郁症状的关系中起调节作用。     

Inhibition and Disinhibition of Male Aggression Against Females: A Personality Moderator Approach

Three experiments examined the role of individual differences in combination with contextual factors hypothesized to moderate the level of hostility toward females evident in male participants' responses. In Study I, we manipulated survey context and examined the influence of participants' levels of rape myth acceptance (RMA) on self-reported rape likelihood. In Study 2, we examined the interactive role of target gender and participants' levels of sex guilt (SG) on aggression toward the target after exposure to an erotic film. Study 3 results suggested that high SG males have particularly negative responses to women (but not men) who enjoy erotic presentations, consistent with a "Jack-the-Ripper" interpretation of the Study 2 findings.     

Opportunities and Issues in Modeling Intensive Longitudinal Data: Learning from the COGITO Project

Abstract

Technological developments increasingly permit the collection of longitudinal data sets in which the data structure contains a large number of participants N and a large number of measurement occasions T. Promising new dynamical systems approaches to the analysis of large N, large T data sets have been proposed that utilize both between-subjects and within-subjects information. The COGITO project, begun over a decade ago, is an early large N?=?204, large T?=?100 study that collected high quality cognitive and psychosocial data. In this introduction, I describe the COGITO project and conceptual and statistical issues that arise in the analysis of large N, large T data sets. I provide a brief overview of the five papers in the special section which include conceptual pieces, a didactic presentation of a dynamic structural equation approach, and papers reporting new statistical analyses of the COGITO data set to answer substantive questions. Although many challenges remain, these new approaches offer the promise of improving scientific inquiry in the behavioral sciences.     

Family Environment as a Moderator of the Association between Conduct Disorder and Suicidality

This study examined whether perceived family support and conflict moderate the relationship between conduct disorder (CD) and suicide attempts (SAs) in a sample of 185 psychiatrically hospitalized adolescents, ages 13 to 18, and their parents. Data were collected using the Schedule for Affective Disorders and Schizophrenia for School Aged Children (K–SADS–PL), the Survey of Children’s Social Support Scale–Short Version, and the Conflict Behavior Questionnaire. Binary logistic regression and simple slope analyses were conducted to test study hypotheses. Results suggest that perceptions of family support, but not conflict, moderate the association between CD and SAs. Specifically, adolescents diagnosed with CD were found to be at heightened risk for an SA if they reported lower family support. These results suggest that clinicians who treat adolescents with CD should assess for perceptions of family support. Incorporating family work into treatment could help to prevent SAs.     

Incorporating Mobility in Growth Modeling for Multilevel and Longitudinal Item Response Data

Multilevel data often cannot be represented by the strict form of hierarchy typically assumed in multilevel modeling. A common example is the case in which subjects change their group membership in longitudinal studies (e.g., students transfer schools; employees transition between different departments). In this study, cross-classified and multiple membership models for multilevel and longitudinal item response data (CCMM-MLIRD) are developed to incorporate such mobility, focusing on students' school change in large-scale longitudinal studies. Furthermore, we investigate the effect of incorrectly modeling school membership in the analysis of multilevel and longitudinal item response data. Two types of school mobility are described, and corresponding models are specified. Results of the simulation studies suggested that appropriate modeling of the two types of school mobility using the CCMM-MLIRD yielded good recovery of the parameters and improvement over models that did not incorporate mobility properly. In addition, the consequences of incorrectly modeling the school effects on the variance estimates of the random effects and the standard errors of the fixed effects depended upon mobility patterns and model specifications. Two sets of large-scale longitudinal data are analyzed to illustrate applications of the CCMM-MLIRD for each type of school mobility.     

Voluntariness of Association as a Moderator of the Importance of Procedural and Distributive Justice

Tyler (1986) proposed that procedural justice was a more important factor in the evaluation of institutions when an individual's association with same was forced or compelled than when the association was voluntary. Unfortunately, Tyler's induction of a moderator effect was based upon questionable interpretations of data, and no deductive attempt was made to explain the phenomenon in theoretical terms. The present study confirmed the moderator effect of voluntariness of association by examining the patterns of correlations between institutional evaluations and procedural justice under two conditions—for members and non-members of open shop (voluntary association) and agency shop (compelled association) unions. The concept of personal control was used to account for the moderator     

Value as a Moderator in Subjective Well-Being

We investigated individual differences in the processes of subjective well-being (SWB). There were considerable individual differences in the domain that was most strongly associated with global life satisfaction. Individuals also differed significantly in the types of activities that they found satisfying. Moreover, these individual differences in the patterns of SWB were systematically related to value orientations. A 23-day daily diary study revealed that intraindividual changes in satisfaction were strongly influenced by the degree of success in the domains that individuals value. The present findings highlight the meaningful individual differences in the qualitative aspects of subjective well-being.     

大数据社会治理研究的理论进展与政策堕距分析

社会治理主要表现为体制和政策的调整。政策的稳定性和创新性既是明确社会治理方向的条件,也是提高社会治理水平的指导。本文在对国内外大数据社会治理研究经验展开充分分析的基础上,以现实问题为例,运用内容分析和语义关系分析细致呈现了现有政策与公众期望之间的差距,以期在政策堕距的分析中总结大数据社会治理的经验。     

Modeling Incomplete Longitudinal Substance Use Data Using Latent Variable Growth Curve Methodology

Longitudinal data sets typically suffer from attrition and other forms of missing data. When this common problem occurs, several researchers have demonstrated that correct maximum likelihood estimation with missing data can be obtained under mild assumptions concerning the missing data mechanism. With reasonable substantive theory, a mixture of cross-sectional and longitudinal methods developed within multiple-group structural equation modeling can provide a strong basis for inference about developmental change. Using an approach to the analysis of missing data, the present study investigated developmental trends in adolescent (N = 759) alcohol, marijuana, and cigarette use across a 5-year period using multiple-group latent growth modeling. An associative model revealed that common developmental trends existed for all three substances. Age and gender were included in the model as predictors of initial status and developmental change. Findings discuss the utility of latent variable structural equation modeling techniques and missing data approaches in the study of developmental change.     

The Association Between Maternal Control and Sense of Coherence in Chinese Adolescents: Self-Efficacy as a Mediator and Stressful Life Events as a Moderator

Journal of Happiness Studies - Both parental support and overprotection have been found to be associated with adolescents’ sense of coherence (SOC) in prior studies. It is unclear, however,...     

A Hierarchical Rater Model for Longitudinal Data

Research studies in psychology and education often seek to detect changes or growth in an outcome over a duration of time. This research provides a solution to those interested in estimating latent traits from psychological measures that rely on human raters. Rater effects potentially degrade the quality of scores in constructed response and performance assessments. We develop an extension of the hierarchical rater model (HRM), which yields estimates of latent traits that have been corrected for individual rater bias and variability, for ratings that come from longitudinal designs. The parameterization, called the longitudinal HRM (L-HRM), includes an autoregressive time series process to permit serial dependence between latent traits at adjacent timepoints, as well as a parameter for overall growth. We evaluate and demonstrate the feasibility and performance of the L-HRM using simulation studies. Parameter recovery results reveal predictable amounts and patterns of bias and error for most parameters across conditions. An application to ratings from a study of character strength demonstrates the model. We discuss limitations and future research directions to improve the L-HRM.     

A Hierarchical Modeling Approach to Data Analysis and Study Design in a Multi-site Experimental fMRI Study

We propose a hierarchical Bayesian model for analyzing multi-site experimental fMRI studies. Our method takes the hierarchical structure of the data (subjects are nested within sites, and there are multiple observations per subject) into account and allows for modeling between-site variation. Using posterior predictive model checking and model selection based on the deviance information criterion (DIC), we show that our model provides a good fit to the observed data by sharing information across the sites. We also propose a simple approach for evaluating the efficacy of the multi-site experiment by comparing the results to those that would be expected in hypothetical single-site experiments with the same sample size.     

DataToText: A Consumer-Oriented Approach to Data Analysis

DataToText is a project developed where the user communicates the relevant information for an analysis and DataToText computer routine produces text output that describes in words, tables, and figures the results from the analyses. Two extended examples are given, one an example of a moderator analysis and the other an example of a dyadic data analysis. The advantages and disadvantages of DataToText are discussed in terms of the statement of the problem, the steps in the analysis, and understanding the meaning of the results. Also discussed is the potential role of DataToText in pedagogy. Although there are some clear deficiencies in a DataToText analysis, it is argued that, more often than not, DataToText will lead to better analyses. Finally, a call is made for methodologists to become more consumer oriented by providing researchers with tools to facilitate the use of methodological developments.     

Item Characteristic Curve Estimation of Signal Detection Theory-Based Personality Data: A Two-Stage Approach to Item Response Modeling

Signal Detection Theory (SDT; MacMillan & Creelman, 1991) is a method of data collection that has been used for several years, which describes the decision-making strategies of individuals. However, its use has been largely restricted to experiments involving sensation and perception. The Overclaiming Questionnaire (OCQ; Paulhus & Bruce, 1990) is a scale that has been developed to measure intellectual ability and personality, using SDT as a guideline. Although the scale has been successful in measuring human characteristics such as narcissism and intelligence, it is still unclear how to measure the characteristics of the various stimuli used (e.g., item difficulty, item discrimination, etc.). In some ways, this is a direct consequence of the general lack of research involved in item parameter estimation in the field of SDT. Using the OCQ, this article presents a graphical and nonparametric form of item response modeling to address this issue. In many ways, the approach is influenced by and structured around item response theory (IRT; Hambleton, Swaminathan, & Rogers, 1991). The general features of both SDT and IRT are described. Results suggest that this method is indeed a reasonable approach to describing item functioning, and there are several advantages to using this method over traditional IRT methods. Furthermore, SDT appears to be a fruitful approach to assessing intelligence, ability, and other psychological constructs, with advantages over traditional approaches. Overall, the results provide interesting implications for item selection and test development in several scientific and academic fields.