Rickard Carlsson

Neuropsychological functions predict 1‐ and 3‐year outcome in first‐episode psychosis

Objective:  To examine neuropsychological performance as a possible predictor of course and outcome in first‐episode psychotic (FEP) patients.

Warm and Competent Hassan = Cold and Incompetent Eric: A Harsh Equation of Real-Life Hiring Discrimination

In a field experiment, we sent out 5,636 job applications varying how Swedish (in-group) and Arab (out-group) applicants presented themselves in terms of two fundamental dimensions of social judgment: warmth and competence. Results indicate substantial discrimination where Arab applicants receive fewer invitations to job interviews. Conveying a warmer or more competent personality increases invitations. However, appearing both warm and competent seems to be especially important for Arab applicants. Arab applicants need to appear warmer and more competent than Swedish applicants to be invited equally often. The practical importance of signaling warmth and competence in labor market contexts is discussed.

Justify your alpha

In response to recommendations to redefine statistical significance to P ≤ 0.005, we propose that researchers should transparently report and justify all choices they make when designing a study, including the alpha level.

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 IATs 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.

Many analysts, one dataset: Making transparent how variations in analytical choices affect results

Twenty-nine teams involving 61 analysts used the same data set to address the same research question: whether soccer referees are more likely to give red cards to dark-skin-toned players than to light-skin-toned players. Analytic approaches varied widely across the teams, and the estimated effect sizes ranged from 0.89 to 2.93 (Mdn = 1.31) in odds-ratio units. Twenty teams (69%) found a statistically significant positive effect, and 9 teams (31%) did not observe a significant relationship. Overall, the 29 different analyses used 21 unique combinations of covariates. Neither analysts’ prior beliefs about the effect of interest nor their level of expertise readily explained the variation in the outcomes of the analyses. Peer ratings of the quality of the analyses also did not account for the variability. These findings suggest that significant variation in the results of analyses of complex data may be difficult to avoid, even by experts with honest intentions. Crowdsourcing data analysis, a strategy in which numerous research teams are recruited to simultaneously investigate the same research question, makes transparent how defensible, yet subjective, analytic choices influence research results.

Ambivalent stereotypes link to peace, conflict, and inequality across 38 nations

Significance Stereotypes reflect a society’s inequality and conflict, providing a diagnostic map of intergroup relations. This stereotype map’s fundamental dimensions depict each group’s warmth (friendly, sincere) and competence (capable, skilled). Some societies cluster groups as high on both (positive “us”) vs. low on both (negative “them”). Other societies, including the United States, have us-them clusters but add ambivalent ones (high on one dimension, low on the other). This cross-national study shows peace-conflict predicts ambivalence. Extremely peaceful and conflictual nations both display unambivalent us-them patterns, whereas intermediate peace-conflict predicts high ambivalence. Replicating previous work, higher inequality predicts more ambivalent stereotype clusters. Inequality and intermediate peace-conflict each use ambivalent stereotypes, explaining complicated intergroup relations and maintaining social system stability. A cross-national study, 49 samples in 38 nations (n = 4,344), investigates whether national peace and conflict reflect ambivalent warmth and competence stereotypes: High-conflict societies (Pakistan) may need clearcut, unambivalent group images distinguishing friends from foes. Highly peaceful countries (Denmark) also may need less ambivalence because most groups occupy the shared national identity, with only a few outcasts. Finally, nations with intermediate conflict (United States) may need ambivalence to justify more complex intergroup-system stability. Using the Global Peace Index to measure conflict, a curvilinear (quadratic) relationship between ambivalence and conflict highlights how both extremely peaceful and extremely conflictual countries display lower stereotype ambivalence, whereas countries intermediate on peace-conflict present higher ambivalence. These data also replicated a linear inequality–ambivalence relationship.

Bayes Factors From Pooled Data Are No Substitute for Bayesian Meta-Analysis: Commentary on Scheibehenne, Jamil, and Wagenmakers (2016)

Scheibehenne, Jamil, and Wagenmakers (2016; SJW) recently introduced Bayesian evidence synthesis (BES). They used it to combine evidence from seven published studies that examined the influence of ...

Between-litter variation in developmental studies of hormones and behavior: inflated false positives and diminished power

Developmental studies of hormones and behavior often include littermates-rodent siblings that share early-life experiences and genes. Due to between-litter variation (i.e., litter effects), the statistical assumption of independent observations is untenable. In two literatures-natural variation in maternal care and prenatal stress-entire litters are categorized based on maternal behavior or experimental condition. Here, we (1) review both literatures; (2) simulate false positive rates for commonly used statistical methods in each literature; and (3) characterize small sample performance of multilevel models (MLM) and generalized estimating equations (GEE). We found that the assumption of independence was routinely violated (>85%), false positives (α=0.05) exceeded nominal levels (up to 0.70), and power (1-β) rarely surpassed 0.80 (even for optimistic sample and effect sizes). Additionally, we show that MLMs and GEEs have adequate performance for common research designs. We discuss implications for the extant literature, the field of behavioral neuroendocrinology, and provide recommendations.

Prototypes and same-gender bias in perceptions of hiring discrimination

ABSTRACT The present study investigated the relative importance of two explanations behind perceptions of gender discrimination in hiring: prototypes and same-gender bias. According to the prototype explanation, people perceive an event as discrimination to the extent that it fits their preconceptions of typical discrimination. In contrast, the same-gender bias explanation asserts that people more readily detect discrimination toward members of their own gender. In four experiments (n = 797), women and men made considerably stronger discrimination attributions, and were moderately more discouraged from seeking work, when the victim was female rather than male. Further, a series of regressions analyses showed beliefs in discrimination of women to be moderately correlated with discrimination attributions of female victims, but little added explanatory value of participant gender, stigma consciousness, or feminist identification. The results offer strong support for the prototype explanation.