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.     

The time course of competition for attention: attention is initially labile

Competition for attention between 2 written words was investigated by presenting the words briefly in a single stream of distractors (Experiment 1) or in different streams (Experiment 2-6), using rapid serial visual presentation at 53 ms/item. Stimulus onset asynchrony (SOA) was varied from 0 to 213 ms. At all SOAs there was strong competition, but which word was more likely to be reported shifted markedly with SOA. At SOAs in the range of 13-53 ms the second word was more likely to be reported, but at 213 ms, the advantage switched to the first word, as in the attentional blink. A 2-stage competition model of attention is proposed in which attention to a detected target is labile in Stage 1. Stage 1 ends when one target is identified, initiating a serial Stage 2 process of consolidation of that target.     

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.     

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.     

Mechanisms of source confusion and discounting in short-term priming: 1. Effects of prime duration and prime recognition

Huber, Shriffrin, Lyle, and Ruys (2001) measured short-term repetition priming effects in perceptual identification with two-alternative forced-choice testing. There was a preference to choose repeated words following passive viewing of primes and a preference against choosing repeated words following active responding to primes. In this present study, we explored conditions of prime processing that produce this pattern of results. Experiment 1 revealed that increased prime duration under passive viewing instructions produces the active priming pattern. Experiment 2 assessed memory for primes: With poor recognition of primes, there was a strong preference for repeated words; however, with good recognition of primes, this preference was eliminated. These results are modeled by a computational theory of optimal decision making, responding optimally with unknown sources of evidence (ROUSE). In ROUSE, a preference for repeated words results from source confusion between primes and choice words. A reversal in the direction of preference arises from the discounting of words known to have also appeared as primes.     

How does background information improve memory for text content?

In two experiments, we investigated whether reading background information benefits memory for text content by influencing the amount of content encoded or the organization of the encoded content. In Experiment 1, half of the participants read background information about the issues to be discussed in the text material, whereas half did not. All the participants were then tested for free recall and cued recall of text content. Free recall was greater for individuals who read issue information than for those who did not. The groups did not differ on cued recall, suggesting that background information did not facilitate the encoding of more text content. Measures of representational organization indicated that increased recall in the issue information group resulted from better organization of content in memory. Experiment 2 extended these findings, using background information about text sources, demonstrated that the efficacy of background information depends on the semantic relationship between that information and text content.