Dyadic judgments based on conflicting samples: The failure to ignore invalid input

The present research demonstrates a so far unrecognized impediment of group performance, metacognitive myopia (Fiedler, 2012). Judges and decision-makers follow the given samples of information uncritically and neglect the metacognitive assessment of the samples' validity. Applying this notion to dyadic judgments, we instructed dyads to jointly estimate conditional probabilities p (Win|A) and p (Win|B) of Lotteries A and B. One person per dyad experienced a valid sample (winning rates conditional on lotteries). The other person experienced an invalid, reverse sample (lotteries conditional on winning). Whereas valid samples provide unbiased estimates of lotteries' winning probabilities, invalid samples can greatly misrepresent the association of winning and lotteries (depending on lottery base rates). Across three experiments, metacognitive myopia—both at the individual and at the dyadic group level—prevented participants from discriminating valid and invalid samples. Group judgments were biased toward erroneous implications of invalid samples, reflecting an equality bias among unequal group members.     

Causal graphical views of fixed effects and random effects models

Despite the long-standing discussion on fixed effects (FE) and random effects (RE) models, how and under what conditions both methods can eliminate unmeasured confounding bias has not yet been widely understood in practice. Using a simple pretest–posttest design in a linear setting, this paper translates the conventional algebraic formalization of FE and RE models into causal graphs and provides intuitively accessible graphical explanations about their data-generating and bias-removing processes. The proposed causal graphs highlight that FE and RE models consider different data-generating models. RE models presume a data-generating model that is identical to a randomized controlled trial, while FE models allow for unobserved time-invariant treatment–outcome confounding. Augmenting regular causal graphs that describe data-generating processes by adding the computational structures of FE and RE estimators, the paper visualizes how FE estimators (gain score and deviation score estimators) and RE estimators (quasi-deviation score estimators) offset unmeasured confounding bias. In contrast to standard regression or matching estimators that reduce confounding bias by blocking non-causal paths via conditioning, FE and RE estimators offset confounding bias by deliberately creating new non-causal paths and associations of opposite sign. Though FE and RE estimators are similar in their bias-offsetting mechanisms, the augmented graphs reveal their subtle differences that can result in different biases in observational studies.     

An integrated model of social psychological and personality psychological perspectives on personality and wellbeing

This article uses multi-rater data from 458 triads (students, mother, father, total N = 1374) to examine the relationship of personality ratings with wellbeing ratings, using a multi-method approach to separate accurate perceptions (shared across raters) from biased perceptions of the self (rater-specific variance). The social-psychological perspective predicts effects of halo bias in self-ratings on wellbeing, whereas the personality-psychological perspective predicts effects of personality traits on wellbeing. Results are more consistent with the personality perspective in that neuroticism (negative), extraversion, agreeableness, and to a lesser extent conscientiousness predicted wellbeing, whereas positive illusions about the self were only weakly and not significantly related to wellbeing. These results cast doubt on the hypothesis that self-enhancement is beneficial for wellbeing.     

Effect of racial bias on composite construction

We investigated how prior bias about a face's racial characteristics can affect its encoding and resultant facial composite construction. In total, 61 participants (24 Europeans, 18 Indians living in India and 19 Indians living in Europe) saw a racially ambiguous unfamiliar face and were led to believe it was either European or Indian. They created a composite of this face, using EFIT6. Two groups of independent raters (one Indian, the other European) then assessed the apparent race of each composite. A different two groups (one Indian, one European) assessed each composite's degree of resemblance to the target face, to determine whether this was influenced by the constructors' initial categorisation of the target face as “own-race” or “other-race.” Composites appeared significantly more “Asian” or “European” according to the bias induced in their creators, but there was no evidence of any own-race bias in the resemblance ratings for the composites.     

A computational account of the development of the generalization of shape information

Abecassis, Sera, Yonas, and Schwade (2001) showed that young children represent shapes more metrically, and perhaps more holistically, than do older children and adults. How does a child transition from representing objects and events as undifferentiated wholes to representing them explicitly in terms of their attributes? According to RBC (Recognition‐by‐Components theory; Biederman, 1987 ), objects are represented as collections of categorical geometric parts (“geons”) in particular categorical spatial relations. We propose that the transition from holistic to more categorical visual shape processing is a function of the development of geon‐like representations via a process of progressive intersection discovery. We present an account of this transition in terms of DORA ( Doumas, Hummel, & Sandhofer, 2008 ), a model of the discovery of relational concepts. We demonstrate that DORA can learn representations of single geons by comparing objects composed of multiple geons. In addition, as DORA is learning it follows the same performance trajectory as children, originally generalizing shape more metrically/holistically and eventually generalizing categorically.     

The desirability bias in predictions: Going optimistic without leaving realism

Does desire for an outcome inflate optimism? Previous experiments have produced mixed results regarding the desirability bias, with the bulk of supportive findings coming from one paradigm—the classic marked-card paradigm in which people make discrete predictions about desirable or undesirable cards being drawn from decks. We introduce a biased-guessing account for the effects from this paradigm, which posits that people are often realistic in their likelihood assessments, but when making a subjectively arbitrary prediction (a guess), they will tend to guess in a desired direction. In order to establish the validity of the biased-guessing account and to distinguish it from other accounts, we conducted five experiments that tested the desirability bias within the paradigm and novel extensions of it. In addition to supporting the biased-guessing account, the findings illustrate the critical role of moderators (e.g., type of outcome, type of forecast) for fully understanding and predicting desirability biases.     

When consensus counts: Exploring the impact of consensus claims in advertising

Consensus claims are broad declarative statements used in an advertisement purporting that a majority of a certain group of consumers prefer or use the sponsor's product or service. While consensus claims are frequently used by advertisers, little is known about how they operate or their effectiveness. We utilize attribution theory to provide insight about how consensus claims operate, and to investigate the impact of consensus claims on attributions and brand attitudes. Results suggest consensus claims are an effective advertising strategy, but their persuasive impact varies according to the featured social information and the processing motivation of audience members.     

Processing efficiency in anxiety: Evidence from eye-movements during visual search

It is generally held that anxiety is characterized by an attentional bias for threatening information. In recent years there has been an important debate whether these biases reside at the level of attentional selection (threat detection) or attentional processing after threat detection (attentional disengagement). In a visual search task containing emotional facial expressions, eye-movements were examined before and after threat detection in high and low trait anxious individuals to further elucidate the temporal unfolding of attentional bias. Results indicated that high-anxious individuals neither showed facilitated orienting to threat nor impaired disengagement of visual attention from threat. Interestingly, the presence of threat in the visual search display was associated with increased decision times in high-anxious individuals. These results challenge some of the current views on attentional bias to threat but indicate that emotional information reduces processing efficiency in anxiety.     

Is manipulation of mood a critical component of cognitive bias modification procedures?

This paper investigates whether changes in mood state are an important component of cognitive bias modification (CBM) procedures. In a novel CBM procedure participants read either positive or negative statements relating to social issues for 5 min. Interpretation bias was measured by means of a scrambled sentence test, which was presented both before and after the CBM procedure. Participants who read the positive statements made more positive resolutions to the scrambled sentences, while participants who read the negative statements made more negative resolutions. Thus, the appropriate positive and negative interpretative biases were induced by the CBM procedure. However, significant mood changes also occurred following CBM. In Experiment 2, a musical mood induction procedure was presented with depressing or elating music. As before, a scrambled sentence test was presented both before and after the musical mood induction. Mood changed in accordance with the valence of the music to the same extent as with CBM. Critically however, performance on the scrambled sentence task did not change for both groups. This demonstrates that a change in mood state is not sufficient for a change in cognitive bias to occur.     

Interpretation bias and depressive symptoms: The role of self-relevance

Cognitive theories of depression emphasize negatively biased interpretations as an important target of therapy. Much of the research on interpretation bias in depression has focused on selection, or deciding which of several interpretations is likely. However, depressive biases may also exist in the generation of possible interpretations, or the ability to think of positive alternatives. If biases exist for generation as well as selection, therapeutic techniques to encourage the generation of more positive interpretations would be warranted. Asking therapy clients to consider someone else in a similar situation is a commonly used therapy strategy but has not been sufficiently examined empirically. In the current studies, we examine interpretation generation and selection in dysphoric and nondysphoric individuals, and contrast interpretations made for the self to interpretations made for two types of “other.” Our studies reveal depressive biases in both interpretation generation and selection, and indicate that interpretation valence is highly sensitive to the type of other considered. All participants generated and selected significantly more positive interpretations for friends than for themselves, but generated significantly more negative interpretations for hypothetical others than for themselves. Our results suggest that encouraging dysphoric individuals to imagine others can be beneficial, but the type of “other” used is critically important, with instructions to consider a close friend most likely to be effective in decreasing negativity in interpretation.