An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents’ preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables while the latter is used for identifying relatively homogeneous clusters of respondents. The proposed method offers an integrated graphical display that provides information on cluster-based structures inherent in multivariate categorical data as well as the interdependencies among the data. An empirical application is presented which demonstrates the usefulness of the proposed method and how it compares to several extant approaches. The work reported in this paper was supported by Grant 290439 and Grant A6394 from the Natural Sciences and Engineering Research Council of Canada to the first and third authors, respectively. We wish to thank Ulf B?ckenholt, Paul Green, and Marc Tomiuk for their insightful comments on an earlier version of this paper. We also wish to thank Byunghwa Yang for generously providing us with his data.     

Cognitive-Behavioral Therapy With Chinese Americans: Research, Theory, and Clinical Practice

In this article, we discuss how to conduct cognitive-behavioral therapy with Chinese Americans. We present an integration of theory, research, and clinical practice to help mental health practitioners understand how Chinese culture may potentially influence the CBT treatment process for Chinese immigrants. Several recommendations are provided as to how to adapt and modify CBT to better meet the therapeutic needs of Chinese American clients. A case example demonstrates how cultural modifications of CBT can lead to effective psychotherapy outcomes for Chinese American clients.     

Emotional reactions to crime across cultures

Information about the emotions experienced by observers when they witness crimes would have important theoretical and practical implications, but to date no study has broadly assessed such emotional reactions. This study addressed this gap in the literature. Observers in seven countries viewed seven videos portraying actual crimes and rated their emotional reactions to each using 14 emotion scales. Observers reported significantly high levels of negative emotions including anger, contempt, disgust, fear and sadness‐related emotions, and anger, contempt and disgust were the most salient emotions experienced by viewers across all countries. Witnesses also reported significantly high levels of positive emotions as well (compared to not feeling the emotion at all), which was unexpected. Country moderated the emotion ratings; post‐hoc analyses indicated that masculine‐oriented cultures reported less nervousness, surprise, excitement, fear and embarrassment than feminine cultures.     

A comparative evaluation of factor- and component-based structural equation modelling approaches under (in)correct construct representations

Structural equation modelling (SEM) has evolved into two domains, factor-based and component-based, dependent on whether constructs are statistically represented as common factors or components. The two SEM domains are conceptually distinct, each assuming their own population models with either of the statistical construct proxies, and statistical SEM approaches should be used for estimating models whose construct representations correspond to what they assume. However, SEM approaches have often been evaluated and compared only under population factor models, providing misleading conclusions about their relative performance. This is partly because population component models and their relationships have not been clearly formulated. Also, it is of fundamental importance to examine how robust SEM approaches can be to potential misrepresentation of constructs because researchers may often lack clear theories to determine whether a factor or component is more representative of a given construct. Addressing these issues, this study begins by clarifying several population component models and their relationships and then provides a comprehensive evaluation of four SEM approaches – the maximum likelihood approach and factor score regression for factor-based SEM as well as generalized structured component analysis (GSCA) and partial least squares path modelling (PLSPM) for component-based SEM – under various experimental conditions. We confirm that the factor-based SEM approaches should be preferred for estimating factor models, whereas the component-based SEM approaches should be chosen for component models. Importantly, the component-based approaches are generally more robust to construct misrepresentation than the factor-based ones. Of the component-based approaches, GSCA should be chosen over PLSPM, regardless of whether or not constructs are misrepresented.     

Social influence in investigative interviews: The effects of reciprocity

This study examined how a principle of social influence—reciprocity—affects the informational elements produced in an investigative interview. Participants from 3 ethnic/cultural groups recruited from the community either received a bottle of water or not prior to their engaging in an investigative interview, in which they either told the truth or lied about having committed a mock crime. Three different informational elements (Relevant details, Irrelevant details, and Plausibility) were coded from their responses, and rapport in the interaction was coded from video. Offering water facilitated greater rapport and influenced the informational elements. These effects were moderated by Veracity condition: For liars, offering water produced more Relevant details and greater Plausibility in the statements and this effect was mediated by rapport. Ethnicity/culture did not moderate these findings. These findings suggested the applicability of principles of social influence in investigative interviews across cultures/ethnicities and had theoretical, empirical, and practical implications.     

Extending Religion-Health Research to Secular Minorities: Issues and Concerns

Claims about religion’s beneficial effects on physical and psychological health have received substantial attention in popular media, but empirical support for these claims is mixed. Many of these claims are tenuous because they fail to address basic methodological issues relating to construct validity, sampling methods or analytical problems. A more conceptual problem has to do with the near universal lack of atheist control samples. While many studies include samples of individuals classified as “low spirituality” or religious “nones”, these groups are heterogeneous and contain only a fraction of members who would be considered truly secular. We illustrate the importance of including an atheist control group whenever possible in the religiosity/spirituality and health research and discuss areas for further investigation.     

Expressed Emotion,Appraisal and Coping by Patients with Recent-onset Schizophrenia: A Pilot Investigation

This pilot study sought to follow up on indications that patients from households with high levels of expressed emotion (EE) differ from those from households with low levels of EE in ways not assessed in typical symptom rating profiles. We examined how patients appraised and coped with a prominent societal stressor. Soon after the start of the Gulf War, 22 patients with recent-onset schizophrenia living in Los Angeles appraised the stressor and completed a coping questionnaire. Results indicated that patients from high-EE homes were likely to use emotion-based confrontational methods to cope with the crisis, while patients from low-EE environments were likely to use avoidance and denial. Patients from high-EE homes thus coped with this non-familial, societal stressor in a way similar to the way in which they have been observed to cope with family conflict: they more readily expressed their anger and frustration than patients from low-EE homes. These pilot data suggest that increased attention should be directed toward those patient behaviours that may be associated with either an increase or decrease in negative affective behaviour from relatives. It may also be fruitful to consider more broadly the adaptive and maladaptive features of the preferred coping strategies of patients from high-EE and low-EE environments.     

Fuzzy Clusterwise Growth Curve Models via Generalized Estimating Equations: An Application to the Antisocial Behavior of Children

The growth curve model has been a useful tool for the analysis of repeated measures data. However, it is designed for an aggregate-sample analysis based on the assumption that the entire sample of respondents are from a single homogenous population. Thus, this method may not be suitable when heterogeneous subgroups exist in the population with qualitatively distinct patterns of trajectories. In this paper, the growth curve model is generalized to a fuzzy clustering framework, which explicitly accounts for such group-level heterogeneity in trajectories of change over time. Moreover, the proposed method estimates parameters based on generalized estimating equations thereby relaxing the assumption of correct specification of the population covariance structure among repeated responses. The performance of the proposed method in recovering parameters and the number of clusters is investigated based on two Monte Carlo analyses involving synthetic data. In addition, the empirical usefulness of the proposed method is illustrated by an application concerning the antisocial behavior of a sample of children.