The role of ethnic identity and self-construal in coping among African American and Caucasian American seventh graders: an exploratory analysis of within-group variance

Much coping research has been conducted comparing members of different ethnic groups using discrete racial classifications. However, the past two decades have seen the construct of ethnicity evolve into a complex variable that must be assessed in a more comprehensive way. This study explored how ethnicity, a discrete variable, and the continuous variables of a person's ethnic identity and self-construal contribute to the use of particular coping strategies across various situations. One hundred twelve seventh graders (67 African Americans and 45 Caucasian Americans) from three suburban middle schools completed questionnaires assessing ethnic identity, self-construal, and coping strategies for medical, test, and social criticism stressors. Results supported the hypothesis that ethnicity as a discrete variable is not associated with coping, but that ethnic identity and self-construal are. It was also found that high scores on the ethnic identity and self-construal scales were indicative of more positive psychological adjustment. Implications for future research and methodological considerations are discussed.     

Atypical depression: enhanced right hemispheric dominance for perceiving emotional chimeric faces

Two studies compared hemispatial bias for perceiving chimeric faces in patients having either atypical or typical depression and healthy controls. A total of 245 patients having major depressive disorder (MDD) or dysthymia (164 with atypical features) and 115 controls were tested on the Chimeric Faces Test. Atypical depression differed from typical depression and controls in showing abnormally large right hemisphere bias. This was present in patients having either MDD or dysthymia and was not related to anxiety, physical anhedonia, or vegetative symptoms. In contrast, patients having MDD with melancholia showed essentially no right hemisphere bias. This is further evidence that atypical depression is a biologically distinct subtype and underscores the importance of this diagnostic distinction for neurophysiologic studies.     

Crying threshold and intensity in major depressive disorder

Clinical lore suggests that depression is associated with frequent and intense crying. To test these postulations empirically, a standardized cry-evoking stimulus was presented to depressed and nondepressed participants, and their likelihood of crying and the magnitude of crying-related changes in their emotion experience, behavior, and autonomic physiology were compared. Unexpectedly, crying was no more likely in depressed than in nondepressed participants. Within the nondepressed group, participants who cried exhibited increases in the report and display of sadness and had greater cardiac and electrodermal activation than did participants who did not cry. There was less evidence of this crying-related emotional activation within the depressed group. The lack of emotional activation among clinically depressed participants who cried provides a tantalizing clue concerning how emotions are dysregulated in this disorder.     

On normal theory based inference for multilevel models with distributional violations

Data in social and behavioral sciences are often hierarchically organized though seldom normal, yet normal theory based inference procedures are routinely used for analyzing multilevel models. Based on this observation, simple adjustments to normal theory based results are proposed to minimize the consequences of violating normality assumptions. For characterizing the distribution of parameter estimates, sandwich-type covariance matrices are derived. Standard errors based on these covariance matrices remain consistent under distributional violations. Implications of various covariance estimators are also discussed. For evaluating the quality of a multilevel model, a rescaled statistic is given for both the hierarchical linear model and the hierarchical structural equation model. The rescaled statistic, improving the likelihood ratio statistic by estimating one extra parameter, approaches the same mean as its reference distribution. A simulation study with a 2-level factor model implies that the rescaled statistic is preferable.This research was supported by grants DA01070 and DA00017 from the National Institute on Drug Abuse and a University of North Texas faculty research grant. We would like to thank the Associate Editor and two reviewers for suggestions that helped to improve the paper.     

Concise formulas for the standard errors of component loading estimates

Concise formulas for the asymptotic standard errors of component loading estimates were derived. The formulas cover the cases of principal component analysis for unstandardized and standardized variables with orthogonal and oblique rotations. The formulas can be used under any distributions for observed variables as long as the asymptotic covariance matrix for sample covariances/correlations is available. The estimated standard errors in numerical examples were shown to be equivalent to those by the methods using information matrices.The author is indebted to anonymous reviewers for the corrections and suggestions on this study, which have led to improvements of earlier versions of this article.     

A unified approach to exploratory factor analysis with missing data,nonnormal data,and in the presence of outliers

Factor analysis is regularly used for analyzing survey data. Missing data, data with outliers and consequently nonnormal data are very common for data obtained through questionnaires. Based on covariance matrix estimates for such nonstandard samples, a unified approach for factor analysis is developed. By generalizing the approach of maximum likelihood under constraints, statistical properties of the estimates for factor loadings and error variances are obtained. A rescaled Bartlett-corrected statistic is proposed for evaluating the number of factors. Equivariance and invariance of parameter estimates and their standard errors for canonical, varimax, and normalized varimax rotations are discussed. Numerical results illustrate the sensitivity of classical methods and advantages of the proposed procedures.This project was supported by a University of North Texas Faculty Research Grant, Grant #R49/CCR610528 for Disease Control and Prevention from the National Center for Injury Prevention and Control, and Grant DA01070 from the National Institute on Drug Abuse. The results do not necessarily represent the official view of the funding agencies. The authors are grateful to three reviewers for suggestions that improved the presentation of this paper.     

Effects of lexicality and distinctiveness on repetition blindness

The repetition blindness (RB) paradigm developed by K. M. Arnell and P. Jolicoeur (1997) was used to examine effects of lexicality (word vs. nonword target pairs) and target distinctiveness on RB. Distinctiveness was manipulated by having both targets (Experiments 1 and 2) or only the first target (Experiment 3) brighter than nontarget items. All 3 experiments demonstrated strong RB for word targets but no RB for nonword targets. This confirms that RB depends on pre-existing memory representations. In fact, there was repetition facilitation for nonwords in Experiments 2 and 3. These experiments also demonstrated that RB is reduced when targets are distinctive. This finding is better understood interms of RB as a failure of memory rather than as a failure of perception.     

The accuracy of abstracts in psychology journals

This article provides an empirically supported reminder of the importance of accuracy in scientific communication. The authors identify common types of inaccuracies in research abstracts and offer suggestions to improve abstract-article agreement. Abstracts accompanying 13% of a random sample of 400 research articles published in 8 American Psychological Association journals during 1997 and 1998 contained data or claims inconsistent with or missing from the body of the article. Error rates ranged from 8% to 18%, although between-journal differences were not significant. Many errors (63%) were unlikely to cause substantive misinterpretations. Unfortunately, 37% of errors found could be seriously misleading with respect to the data or claims presented in the associated article. Although deficient abstracts may be less common in psychology journals than in major medical journals (R. M. Pitkin, M. A. Branagan, & L. F. Burmeister, 1999), there is still cause for concern and need for improvement.     

Face recognition by hand

We investigated participants' ability to identify and represent faces by hand. In Experiment 1, participants proved surprisingly capable of identifying unfamiliar live human faces using only their sense of touch. To evaluate the contribution of geometric and material information more directly, we biased participants toward encoding faces more in terms of geometric than material properties, by varying the exploration condition. When participants explored the faces both visually and tactually, identification accuracy did not improve relative to touch alone. When participants explored masks of the faces, thereby eliminating material cues, matching accuracy declined substantially relative to tactual identification of live faces. In Experiment 2, we explored intersensory transfer of face information between vision and touch. The findings are discussed in terms of their relevance to haptic object processing and to the face-processing literature in general.     

Category induction from distributional cues in an artificial language

The ability to identify the grammatical category of a word (e.g., noun, verb, adjective) is a fundamental aspect of competence in a natural language. Children show evidence of categorization by as early as 18 months, and in some cases younger. However, the mechanisms that underlie this ability are not well understood. The lexical co-occurrence patterns of words in sentences could provide information about word categories--for example, words that follow the in English often belong to the same category. As a step in understanding the role distributional mechanisms might play in language learning, the present study investigated the ability of adults to categorize words on the basis of distributional information. Forty participants listened for approximately 6 min to sentences in an artificial language and were told that they would later be tested on their memory for what they had heard. Participants were next tested on an additional set of sentences and asked to report which sentences they recognized from the first 6 min. The results suggested that learners performed a distributional analysis on the initial set of sentences and recognized sentences on the basis of their memory of sequences of categories of words. Thus, mechanisms that would be useful in natural language learning were shown to be active in adults in an artificial language learning task.