Constrained maximum likelihood estimation of two-level covariance structure model via EM type algorithms

In this paper, the constrained maximum likelihood estimation of a two-level covariance structure model with unbalanced designs is considered. The two-level model is reformulated as a single-level model by treating the group level latent random vectors as hypothetical missing-data. Then, the popular EM algorithm is extended to obtain the constrained maximum likelihood estimates. For general nonlinear constraints, the multiplier method is used at theM-step to find the constrained minimum of the conditional expectation. An accelerated EM gradient procedure is derived to handle linear constraints. The empirical performance of the proposed EM type algorithms is illustrated by some artifical and real examples.This research was supported by a Hong Kong UCG Earmarked Grant, CUHK 4026/97H. We are greatly indebted to D.E. Morisky and J.A. Stein for the use of their AIDS data in our example. We also thank the Editor, two anonymous reviewers, W.Y. Poon and H.T. Zhu for constructive suggestions and comments in improving the paper. The assistance of Michael K.H. Leung and Esther L.S. Tam is gratefully acknowledged.     

Evaluating the Factor Structure of the MIDI Personality Scale Using Exploratory Structural Equation Modeling

This study investigated the factor structure of the 26‐item Midlife Development Inventory (MIDI) Personality Scale in a sample of 2,720 Americans. It was found that whereas confirmatory factor analysis (CFA) did not provide an acceptable fit to the data, exploratory structural equation modeling (ESEM) provided an acceptable fit. The results of ESEM revealed that the a priori five‐factor structure of personality was generally consistent with the data, and all items had salient loadings on their target factors. ESEM also revealed that some of the items contributed significantly to more than one personality factor. The results are in line with previous research, and indicate that ESEM is more suitable than CFA for the study of personality traits.     

Structure and content of affective associations with health behaviours: Is the behaviour ‘good OR bad’ or ‘good AND bad’

Objective: The feelings and emotions individuals associate with health-related behaviours influence engagement in those behaviours. However, the structure and the content of these affective associations have not been examined. The studies reported here examined competing hypotheses about the structure (unidimensional or bidimensional) and content (generalised affect or specific emotions) of affective associations with two health-related behaviours: physical activity and fruit/vegetable consumption.

Design: For each behaviour, participants (fruit and vegetable consumption n = 149; physical activity n = 199) completed an assessment of the association of 40 positive and 51 negative affect concepts with the behaviour.

Main outcome measures: Ratings of affective associations with each behaviour.

Results: Confirmatory factor analyses comparing unidimensional and bidimensional affect structure models showed that the structure of individuals’ affective associations was bidimensional for both behaviours – positive and negative affective associations were shown to be separate and distinct constructs. Exploratory factor analyses supported a model of affective associations as generalised affect for both behaviours.

Conclusion: Affective associations with both physical activity and with fruit/vegetable consumption consist of separate positive and negative dimensions of generalised affect. These findings lead to recommendations for research and intervention development based on the implications for how affective associations might operate to influence behavioural decision-making.     

进化心理学对心理素质结构研究的整合与重构——以学生心理素质结构研究为例

传统的心理素质结构研究模式不经济,研究结果出现纵向断裂横向分裂的趋势.从进化心理学的视角来看,心理素质结构的最终功能均指向个体的适应性,其形成是与周围环境不断排斥和融合的过程.建构的心理素质结构融合模型能在一定程度上解决传统研究模式的弊端,并建议今后的研究应以分析人为主导转而分析人及其所处的文化环境并重,进而引导人的心理素质结构的不断发展.     

Parental Divorce,Parental Religious Characteristics,and Religious Outcomes in Adulthood

Parental divorce has been linked to religious outcomes in adulthood. Previous research, however, has not adequately accounted for parental religious characteristics, which may render the association spurious and/or moderate the relationship. Many studies also do not consider subsequent family context, namely, whether one's custodial parent remarries. Using pooled data from three waves of the General Social Survey, we examine the nature of the relationships among parental divorce, subsequent family structure, and religiosity in adulthood. Growing up in a single‐parent family—but not a stepparent family—is positively associated with religious disaffiliation and religious switching and negatively associated with regular religious service attendance. Accounting for parental religious characteristics, however, explains sizable proportions of these relationships. In fact, after accounting for parental religious affiliation and service attendance, growing up with a single parent does not have a significant effect on religious service attendance. Parental religiosity also moderates the relationship between growing up with a single parent and religious service attendance: being raised in a single‐parent home does have a negative effect on religious service attendance among adults who had two religiously involved parents. There is modest evidence of this moderating relationship for other religious outcomes. Implications of these findings are discussed.     

An all‐or‐nothing thinking turns into darkness: Relations between dichotomous thinking and personality disorders1

Dichotomous thinking is an individual's propensity to think in terms of binary opposition. While this thinking style may be useful for quick decision‐making, some clinical psychologists have indicated that such a style is related to personality disorders. Oshio (2009 ) revealed that the Dichotomous Thinking Inventory (DTI) has significant positive correlations with borderline personality and narcissism. This study examines whether dichotomous thinking is associated with cluster A, B, and C personality disorders. The participants comprised 152 Japanese undergraduates (84 male and 68 female). They completed the DTI and Ten Personality Styles scale (10 PesT; Nakazawa (2006 )), developed from the definitions of personality disorders in the DSM‐IV. Structural equation modeling supported the hierarchical factor structure of personality disorders. The dichotomous thinking effects “cluster” level of disorders more than other levels. The results indicated that thinking dichotomously may lead to wide‐ranging personality disorders.     

Modeling,Truth, and Philosophy

Knowledge requires truth, and truth, we suppose, involves unflawed representation. Science does not provide knowledge in this sense but rather provides models, representations that are limited in their accuracy, precision, or, most often, both. Truth as we usually think of it is an idealization, one that serves wonderfully in most ordinary applications, but one that can terribly mislead for certain issues in philosophy. This article sketches how this happens for five important issues, thereby showing how philosophical method must take into account the idealized nature of our familiar conception of truth.     

A neurally plausible parallel distributed processing model of event-related potential word reading data

The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between explicit, computational models and physiological data collected during the performance of cognitive tasks, we developed a PDP model of visual word recognition which simulates key results from the ERP reading literature, while simultaneously being able to successfully perform lexical decision—a benchmark task for reading models. Simulations reveal that the model’s success depends on the implementation of several neurally plausible features in its architecture which are sufficiently domain-general to be relevant to cognitive modeling more generally.     

Psychometric qualities of the White Bear Suppression Inventory in a Dutch sample of children and adolescents

The White Bear Suppression Inventory [WBSI; Wegner and Zanakos (1994)] was developed to assess the tendency to suppress unwanted thoughts. Most psychometric studies of the WBSI have included healthy students and adults with obsessive-compulsive disorder. There has been increasing interest in thought suppression in children and adolescents, especially after a traumatic event, but little is known about the psychometric properties of the WBSI for children. The aim of this research was to examine the psychometric qualities of the WBSI in a Dutch sample of children and adolescents. Two studies were conducted. First, the WBSI’s factor structure, internal consistency and test-retest stability were examined in a sample of 203 primary school children (9-13 years). Second, the factor structure and content validity were assessed in 89 children and adolescents (8-18 years) who attended the emergency room after a road traffic accident. Results demonstrated that the WBSI items contribute to a single factor measuring the suppression of unwanted thoughts and that the reliability is satisfactory. Associations between the WBSI and PTSD-symptoms demonstrated sufficient content validity. The findings suggest that the WBSI can appropriately be used in child and adolescent samples.     

A rational analysis of the acquisition of multisensory representations

How do people learn multisensory, or amodal, representations, and what consequences do these representations have for perceptual performance? We address this question by performing a rational analysis of the problem of learning multisensory representations. This analysis makes use of a Bayesian nonparametric model that acquires latent multisensory features that optimally explain the unisensory features arising in individual sensory modalities. The model qualitatively accounts for several important aspects of multisensory perception: (a) it integrates information from multiple sensory sources in such a way that it leads to superior performances in, for example, categorization tasks; (b) its performances suggest that multisensory training leads to better learning than unisensory training, even when testing is conducted in unisensory conditions; (c) its multisensory representations are modality invariant; and (d) it predicts ‘‘missing” sensory representations in modalities when the input to those modalities is absent. Our rational analysis indicates that all of these aspects emerge as part of the optimal solution to the problem of learning to represent complex multisensory environments.