The Dark Triad Traits,Humor Styles,and Schadenfreude: Others' Misery as the Devil's Laughing Stocks1

This research investigated the relationships of the Dark Triad traits, humor styles, and schadenfreude with 169 participants who completed the Short Dark Triad, the Humor Style Questionnaire, and a measure of schadenfreude. Significant correlations imply that those with salient dark traits (psychopathy, Machiavellianism, narcissism) elicit pleasure from others' misfortune. Additionally, schadenfreude can be a product of self-defeating and aggressive humor styles. Indirect effect analysis revealed the significance of the indirect effect of the measured aggressive humor style on the Dark Triad's direct effects on schadenfreude. These results imply that those with salient Dark Triad traits enjoy others' misery as a means to undermine them. Hence, individuals with salient Dark Triad traits tend to engage in downward social comparison.     

Method effects due to social desirability as a parsimonious explanation of the deviation from unidimensionality in LOT-R scores

Dispositional optimism measured by the Life Orientation Test (Revised; LOT-R, Scheier et al., 1994) was originally proposed as a unidimensional construct pertaining to individual differences in positive outcome expectancies. However, factor analytic research has suggested two separate “optimism” and “pessimism” factors associated with positively and negatively worded items respectively. Using confirmatory factor analysis with data from N = 658 students it is shown that a general optimism model with method effects of the positively worded items fits even better than the “optimism–pessimism” model in terms of the AIC statistic, which accounts for both model parsimony and model fit. Furthermore, an attempt is made to explain the method effects by social desirability: impression management, one of two components of socially desirable responding, correlates significantly with the method factor whereas the other component, self-deceptive enhancement, is related to the general optimism factor. Thus it is shown that the deviation from unidimensionality of observed scores does not imply deviation from unidimensionality of optimism when method effects are incorporated in the model.     

The Role of Strategy in Mixed-Gender Group Interactions: A Study of the Television Show “The Weakest Link”

This paper studies mixed-gender group interactions in a strategic game where group members are sequentially eliminated till a single winner takes all. Study 1 tests the hypothesis that female contestants are retained till final rounds where they are eliminated. Using observational data from the US television show The Weakest Link (20 shows), results show that females are finalists but not winners. In a laboratory study (Study 2, 67 Berkeley undergraduates), we show that this effect is attenuated when winnings are shared among finalists (versus one winner takes all) due to the reduction in competitive pressures in the context. This research was supported in part by the Junior Faculty Research Grant awarded by the University of California at Berkeley to the second author.     

大学生对两个原因交互作用效应的评估

用大学生被试的两个实验考察人们对两个原因交互作用效应的定性评估和定量评估。实验结果表明,被试的定性评估与交互作用对比的性质相一致,而与因果力的性质不相一致;被试的定量评估随交互作用对比值增加而增加,而不受因果力的影响。实验结果一致支持交互作用对比标准,而不支持因果力标准和交叉乘积比率标准。这不同于以往的有关研究结果     

Effects of classroom context on university students’ judgments about cheating: mediating and moderating processes

Hypothetical vignettes were used to examine the effects of classroom context variables (pedagogical quality and classroom goal structure) on undergraduate (study 1) and graduate (study 2) students’ judgments about cheating. Consistent with attribution theory and previous findings, poor (versus good) pedagogy and performance (versus mastery) goals structures resulted in more teacher blame and less student blame for cheating, and cheating was rated as more acceptable and more likely in these situations. Participants’ own prior cheating history but not their experience as a classroom teacher also affected these judgments. Relations between classroom context variables and assigned blame for cheating were mediated by students’ assessments of the fairness of the classroom situation.     

How probability theory explains the conjunction fallacy

The conjunction fallacy occurs when people judge a conjunctive statement B‐and‐A to be more probable than a constituent B, in contrast to the law of probability that P(B ∧ A) cannot exceed P(B) or P(A). Researchers see this fallacy as demonstrating that people do not follow probability theory when judging conjunctive probability. This paper shows that the conjunction fallacy can be explained by the standard probability theory equation for conjunction if we assume random variation in the constituent probabilities used in that equation. The mathematical structure of this equation is such that random variation will be most likely to produce the fallacy when one constituent has high probability and the other low, when there is positive conditional support between the constituents, when there are two rather than three constituents, and when people rank probabilities rather than give numerical estimates. The conjunction fallacy has been found to occur most frequently in exactly these situations. Copyright © 2008 John Wiley & Sons, Ltd.     

英语文章阅读过程中的文章标记效应研究

该研究通过三个实验探讨高职生英语阅读的文章标记效应。实验一探讨文章标记对阅读英语长、短文章的影响,结果发现文章标记对英语长文章主题信息保持的促进作用大于对英语短文章主题信息的促进作用。实验二以EyelinkⅡ型眼动仪为工具,考察被试阅读有、无标记文章的主题句的眼动模式的差异,结果发现被试阅读这两类主题句的眼动模式存在显著差异。实验三考察对被试进行文章结构策略训练对文章标记效应的影响,结果发现训练促进了被试对无标记英语长文章主题信息的保持,研究结果支持策略转换假设。     

Identifying Variables Responsible for Data not Missing at Random

When data are not missing at random (NMAR), maximum likelihood (ML) procedure will not generate consistent parameter estimates unless the missing data mechanism is correctly modeled. Understanding NMAR mechanism in a data set would allow one to better use the ML methodology. A survey or questionnaire may contain many items; certain items may be responsible for NMAR values in other items. The paper develops statistical procedures to identify the responsible items. By comparing ML estimates (MLE), statistics are developed to test whether the MLEs are changed when excluding items. The items that cause a significant change of the MLEs are responsible for the NMAR mechanism. Normal distribution is used for obtaining the MLEs; a sandwich-type covariance matrix is used to account for distribution violations. The class of nonnormal distributions within which the procedure is valid is provided. Both saturated and structural models are considered. Effect sizes are also defined and studied. The results indicate that more missing data in a sample does not necessarily imply more significant test statistics due to smaller effect sizes. Knowing the true population means and covariances or the parameter values in structural equation models may not make things easier either. The research was supported by NSF grant DMS04-37167, the James McKeen Cattell Fund.     

Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution then requires an integral equation that is of dimension equal to the number of nonlinear terms. For nonlinear functions that have linear coefficients, the improvement in computational speed and accuracy using the new algorithm can be dramatic. An illustration of the method with repeated measures data from a learning experiment is presented.