Statistical Significance Levels of Nonparametric Tests Biased by Heterogeneous Variances of Treatment Groups

The statistical significance levels of the Wilcoxon-Mann-Whitney test and the Kruskal-Wallis test are substantially biased by heterogeneous variances of treatment groups—even when sample sizes are equal. Under these conditions, the Type I error probabilities of the nonparametric tests, performed at the .01, .05, and .10 significance levels, increase by as much as 40%-50% in many cases and sometimes as much as 300%. The bias increases systematically as the ratio of standard deviations of treatment groups increases and remains fairly constant for various sample sizes. There is no indication that Type I error probabilities approach the significance level asymptotically as sample size increases.     

Significance tests to determine the direction of effects in linear regression models

Previous studies have discussed asymmetric interpretations of the Pearson correlation coefficient and have shown that higher moments can be used to decide on the direction of dependence in the bivariate linear regression setting. The current study extends this approach by illustrating that the third moment of regression residuals may also be used to derive conclusions concerning the direction of effects. Assuming non‐normally distributed variables, it is shown that the distribution of residuals of the correctly specified regression model (e.g., Y is regressed on X) is more symmetric than the distribution of residuals of the competing model (i.e., X is regressed on Y). Based on this result, 4 one‐sample tests are discussed which can be used to decide which variable is more likely to be the response and which one is more likely to be the explanatory variable. A fifth significance test is proposed based on the differences of skewness estimates, which leads to a more direct test of a hypothesis that is compatible with direction of dependence. A Monte Carlo simulation study was performed to examine the behaviour of the procedures under various degrees of associations, sample sizes, and distributional properties of the underlying population. An empirical example is given which illustrates the application of the tests in practice.     

人才甄选中的人格测验作假研究的深入与拓展

企业人才甄选情境下求职者很容易在人格测验中作假。至今有关作假的研究已包含作假的内涵、来源和识别等多个方面,也诞生了多种心理模型尝试解释作假产生的心理机制,如作假动机与作假能力交互作用理论、作假计划行为理论、作假整合模型、一般作假行为模型以及作假的VIE模型,为后续理论研究点明方向。此外,作假应用领域中新兴的网络人格测验作假受到关注,在此介绍网络与纸笔测验两种形式下,人格测验作假行为、作假意向的不同。     

If merely more words,what is the point? A critical response

A critical response is given to the five articles constituting the special issue theme ‘Critical psychotherapy and counselling: if not now, when?’ The related arguments concerning political justice, professional struggles, new public management, therapeutic language use and ecotherapy are considered concisely and challenges made. Into this discussion is injected a degree of ‘brutalist objection’, along with a recommendation for radical honesty, a confession of depressive realism and hints of nihilism. Psychotherapy, whether traditional or critical, is taken to task for its romantic enmeshment in a hubristic fantasy of infinite relevance and improvement.     

An investigation of cognitive test performance across conditions of silence,background noise and music as a function of neuroticism

The present study investigates the role of trait neuroticism on cognitive performance under distraction. Seventy participants were given a personality test and then undertook a number of different cognitive tasks in silence, in the presence of popular music and in background noise. It was predicted that performance on a general intelligence test, a test of abstract reasoning, and a mental arithmetic task would be adversely affected by background sounds. It was predicted that neuroticism would be negatively correlated with performance on the mental arithmetic task but only when the individuals were working in the presence of background sound. Stable vs. unstable participant's performance on a mental arithmetic task during noise was significantly higher as predicted. The results provided partial support for the hypotheses and are discussed with respect to previous findings in the literature on personality (particularly introversion–extraversion) and distraction on cognitive task performance. Limitations are noted.     

Properties of bootstrap tests for N‐of‐1 studies

N‐of‐1 study designs involve the collection and analysis of repeated measures data from an individual not using an intervention and using an intervention. This study explores the use of semi‐parametric and parametric bootstrap tests in the analysis of N‐of‐1 studies under a single time series framework in the presence of autocorrelation. When the Type I error rates of bootstrap tests are compared to Wald tests, our results show that the bootstrap tests have more desirable properties. We compare the results for normally distributed errors with those for contaminated normally distributed errors and find that, except when there is relatively large autocorrelation, there is little difference between the power of the parametric and semi‐parametric bootstrap tests. We also experiment with two intervention designs: ABAB and AB, and show the ABAB design has more power. The results provide guidelines for designing N‐of‐1 studies, in the sense of how many observations and how many intervention changes are needed to achieve a certain level of power and which test should be performed.     

Improving Psychological Measurement: Does It Make a Difference? A Comment on Nesselroade and Molenaar (2016)

Nesselroade and Molenaar advocate the use of an idiographic filter approach. This is a fixed-effects approach, which may limit the number of individuals that can be simultaneously modeled, and it is not clear how to model the presence of subpopulations. Most important, Nesselroade and Molenaar's proposal appears to be best suited for modeling long time series on a few variables for a few individuals. Long time series are not common in psychological applications. Can it be applied to the usual longitudinal data we face? These are characterized by short time series (four to five points in time), hundreds of individuals, and dozens of variables. If so, what do we gain? Applied settings most often involve between-individual decisions. I conjecture that their approach will not outperform common, simpler, methods. However, when intraindividual decisions are involved, their approach may have an edge.     

A closer look at the discrimination outcomes in the IAT literature

To what extent the IAT (Implicit Association Test, Greenwald et al., 1998) predicts racial and ethnic discrimination is a heavily debated issue. The latest meta‐analysis by Oswald et al. (2013) suggests a very weak association. In the present meta‐analysis, we switched the focus from the predictor to the criterion, by taking a closer look at the discrimination outcomes. We discovered that many of these outcomes were not actually operationalizations of discrimination, but rather of other related, but distinct, concepts, such as brain activity and voting preferences. When we meta‐analyzed the main effects of discrimination among the remaining discrimination outcomes, the overall effect was close to zero and highly inconsistent across studies. Taken together, it is doubtful whether the amalgamation of these outcomes is relevant criteria for assessing the IAT's predictive validity of discrimination. Accordingly, there is also little evidence that the IAT can meaningfully predict discrimination, and we thus strongly caution against any practical applications of the IAT that rest on this assumption. However, provided that the application is thoroughly informed by the current state of the literature, we believe the IAT can still be a useful tool for researchers, educators, managers, and students who are interested in attitudes, prejudices, stereotypes, and discrimination.