测评中的共同方法偏差

共同方法变异是指由于测量方法而非所测构想造成的变异。共同方法变异会对测评和测评间的相关产生严重影响,甚至会使研究导致错误结论。本文介绍了学界对共同方法偏差的研究,内容包括：(1)共同方法偏差在多大程度上和以何种方式影响测评研究结果;(2)共同方法偏差的潜在来源及其程序控制。     

The variable nature of cognitive control: a dual mechanisms framework

A core component of cognitive control - the ability to regulate thoughts and actions in accordance with internally represented behavioral goals - might be its intrinsic variability. In this article, I describe the dual mechanisms of control (DMC) framework, which postulates that this variability might arise from qualitative distinctions in temporal dynamics between proactive and reactive modes of control. Proactive control reflects the sustained and anticipatory maintenance of goal-relevant information within lateral prefrontal cortex (PFC) to enable optimal cognitive performance, whereas reactive control reflects transient stimulus-driven goal reactivation that recruits lateral PFC (plus a wider brain network) based on interference demands or episodic associations. I summarize recent research that demonstrates how the DMC framework provides a coherent explanation of three sources of cognitive control variation - intra-individual, inter-individual and between-groups - in terms of proactive versus reactive control biases.     

Multiple Mechanisms of Prime-to-Behavior Effects

Recent research has explored how the activation of social constructs via priming can affect behavior. Multiple mechanisms have received support, including direct activation of behavioral representations, goal activation, biases in person perception, biases in situation perception, and biases in self-perception. We review the evolving complexity of proposed prime-to-behavior mechanisms, discuss the predictions of each mechanism, and suggest some integrative principles that influence how and when primed constructs affect behavior.     

共同方法偏差的统计检验与控制方法

共同方法偏差是心理学研究中一个越来越被关注的课题,但国内心理学界对其的介绍、研究还比较少,导致研究中对共同方法偏差的控制还有所欠缺。共同方法偏差的控制方法分为程序控制和统计控制,该文介绍了共同方法偏差的多种统计控制法,如因素分析法、偏相关法、潜在的误差变量控制法、结构方程模型法等,分析了其各自的优缺点,并提出了如何选择采用这些方法的建议.     

The relative influence of advice from human experts and statistical methods on forecast adjustments

Decision makers and forecasters often receive advice from different sources including human experts and statistical methods. This research examines, in the context of stock price forecasting, how the apparent source of the advice affects the attention that is paid to it when the mode of delivery of the advice is identical for both sources. In Study 1, two groups of participants were given the same advised point and interval forecasts. One group was told that these were the advice of a human expert and the other that they were generated by a statistical forecasting method. The participants were then asked to adjust forecasts they had previously made in light of this advice. While in both cases the advice led to improved point forecast accuracy and better calibration of the prediction intervals, the advice which apparently emanated from a statistical method was discounted much more severely. In Study 2, participants were provided with advice from two sources. When the participants were told that both sources were either human experts or both were statistical methods, the apparent statistical‐based advice had the same influence on the adjusted estimates as the advice that appeared to come from a human expert. However when the apparent sources of advice were different, much greater attention was paid to the advice that apparently came from a human expert. Theories of advice utilization are used to identify why the advice of a human expert is likely to be preferred to advice from a statistical method. Copyright © 2009 John Wiley & Sons, Ltd.     

Imagery and interpretations in social phobia: support for the combined cognitive biases hypothesis

Cognitive-behavioral models of clinical problems typically postulate a role for the combined effects of different cognitive biases in the maintenance of a given disorder. It is striking therefore that research has tended to examine cognitive biases in isolation rather than assessing how they work together to maintain psychological dysfunction. The combined cognitive biases hypothesis presented here suggests that cognitive biases influence each another and can interact to maintain a given disorder. Furthermore, it is proposed that the combined effects of cognitive biases may have a greater impact on sustaining a given disorder than if the biases operated in isolation. The combined cognitive biases hypothesis is examined in relation to imagery and interpretation in social phobia. Individuals with social phobia experience negative images of themselves performing poorly in social situations, and they also interpret external social information in a less positive way than those without social anxiety. Evidence of a reciprocal relationship between imagery and interpretations is presented, and the mechanisms underlying the combined effects are discussed. Clinical implications and the potential utility of examining the combined influence of other cognitive biases are highlighted.     

Methodological Challenges in Causal Research on Racial and Ethnic Patterns of Cognitive Trajectories: Measurement, Selection, and Bias

Research focused on understanding how and why cognitive trajectories differ across racial and ethnic groups can be compromised by several possible methodological challenges. These difficulties are especially relevant in research on racial and ethnic disparities and neuropsychological outcomes because of the particular influence of selection and measurement in these contexts. In this article, we review the counterfactual framework for thinking about causal effects versus statistical associations. We emphasize that causal inferences are key to predicting the likely consequences of possible interventions, for example in clinical settings. We summarize a number of common biases that can obscure causal relationships, including confounding, measurement ceilings/floors, baseline adjustment bias, practice or retest effects, differential measurement error, conditioning on common effects in direct and indirect effects decompositions, and differential survival. For each, we describe how to recognize when such biases may be relevant and some possible analytic or design approaches to remediating these biases.     

Data Collection in a Flat World: The Strengths and Weaknesses of Mechanical Turk Samples

Mechanical Turk (MTurk), an online labor system run by Amazon.com, provides quick, easy, and inexpensive access to online research participants. As use of MTurk has grown, so have questions from behavioral researchers about its participants, reliability, and low compensation. In this article, we review recent research about MTurk and compare MTurk participants with community and student samples on a set of personality dimensions and classic decision‐making biases. Across two studies, we find many similarities between MTurk participants and traditional samples, but we also find important differences. For instance, MTurk participants are less likely to pay attention to experimental materials, reducing statistical power. They are more likely to use the Internet to find answers, even with no incentive for correct responses. MTurk participants have attitudes about money that are different from a community sample's attitudes but similar to students' attitudes. Finally, MTurk participants are less extraverted and have lower self‐esteem than other participants, presenting challenges for some research domains. Despite these differences, MTurk participants produce reliable results consistent with standard decision‐making biases: they are present biased, risk‐averse for gains, risk‐seeking for losses, show delay/expedite asymmetries, and show the certainty effect—with almost no significant differences in effect sizes from other samples. We conclude that MTurk offers a highly valuable opportunity for data collection and recommend that researchers using MTurk (1) include screening questions that gauge attention and language comprehension; (2) avoid questions with factual answers; and (3) consider how individual differences in financial and social domains may influence results. Copyright © 2012 John Wiley & Sons, Ltd.     

Atypical birdsong and artificial languages provide insights into how communication systems are shaped by learning,use, and transmission

In this article, I argue that a comparative approach focusing on the cognitive capacities and behavioral mechanisms that underlie vocal learning in songbirds and humans can provide valuable insights into the evolutionary origins of language. The experimental approaches I discuss use abnormal song and atypical linguistic input to study the processes of individual learning, social interaction, and cultural transmission. Atypical input places increased learning and communicative pressure on learners, so exploring how they respond to this type of input provides a particularly clear picture of the biases and constraints at work during learning and use. Furthermore, simulating the cultural transmission of these unnatural communication systems in the laboratory informs us about how learning and social biases influence the structure of communication systems in the long run. Findings based on these methods suggest fundamental similarities in the basic social–cognitive mechanisms underlying vocal learning in birds and humans, and continuing research promises insights into the uniquely human mechanisms and into how human cognition and social behavior interact, and ultimately impact on the evolution of language.     

Aid and bias

Over the last few decades, psychologists have amassed a great deal of evidence that our thinking is strongly influenced by a number of biases. This research appears to have important implications for moral methodology. It seems likely that these biases affect our thinking about moral issues, and a fuller awareness of them might help us to find ways to counteract their influence, and so to improve our moral thinking. And yet there is little or no reference to such biases in the philosophical literature on many pressing, substantive moral questions. In this paper, I make a start on repairing this omission in relation to one such question, the 'Aid Question', which concerns how much, if anything, we are morally required to give to aid agencies. I begin by sketching a number of biases that seem particularly likely to affect our thinking about that question. I then go on to review the psychological research on 'debiasing' - that is, on attempts to counteract the influence of such biases. And finally I discuss and illustrate certain strategies for counteracting the influence of the biases in question on our thinking about the Aid Question.     

THE EFFECT OF QUALITY CONTROL REVISIONS ON MIXED STANDARD SCALE RATING ERRORS

Evaluations of performance evaluation ratings conventionally use various psychometric criteria, with reliability being the measure most commonly reported. Rating errors have been attributed to a variety of sources, including the statistical properties of the format or content, ratee performance variability, rater biases, and characteristics of the work setting. This article reports research on error statistics that can be generated using the Mixed Standard Scale (MSS) evaluation format. The reduction of system error rates following revision guided by statistical analysis is a clear indication that the quality control features of this format are useful in the management of performance evaluation systems.     

Cultural differences in unrealistic optimism and pessimism: the role of egocentrism and direct versus indirect comparison measures

Recent research has raised questions regarding the consistency of unrealistic optimism and related self-enhancing tendencies, both within cultures and across cultures. The current study tested whether the method used to assess unrealistic optimism influenced cross-cultural patterns in the United States and Japan. The results showed that the direct method (a single comparison judgment between self and peers) produced similar patterns across cultures because of cognitive biases (e.g., egocentrism); specifically, participants were unrealistically optimistic about experiencing infrequent/negative events but pessimistic about experiencing frequent/ negative events. However, the indirect method (separate self- and peer judgments) produced different patterns across cultures because culturally specific motivational biases emerged using this method; specifically, the U.S. sample was more unrealistically optimistic than the Japanese sample. The authors discuss how these results might influence the interpretation of previous findings on culture and self-enhancement.     

Three approaches to the study of infant temperament

In temperament research, the sensitive quantification of individual differences is critical, and biases affecting temperament measures differ somewhat from those affecting normative studies of development. In this paper, we attempt to specify major biases and strengths of the three methods most widely used in the assessment of infant temperament: parent report, home observation, and laboratory observation. We also describe an ongoing research program in order to illustrate how potential biases may be negotiated. We conclude that choice of temperament measure or measures depends upon (a) the purpose of the assessment, (b) knowledge of empirical relations among methods, and (c) evaluations of the seriousness of potential measurement biases.     

Risk of bias in trial-based economic evaluations: Identification of sources and bias-reducing strategies

Objective: The objectives of this article are first to give an overview of the risks of bias in trial-based economic evaluations and, second, to identify how key sources for bias can be revealed and overcome (i.e. what bias-reducing strategies might be employed) in future trial-based economic evaluations in the field of health psychology.

Design: Narrative review discussing sources of bias in trial-based economic evaluations and bias-reducing strategies.

Results: We identified 11 biases and assigned them to a particular trial phase. A distinction is made between pre-trial biases, biases during the trial and biases that are relevant after the actual trial. All potential forms of bias are discussed in detail and strategies are shown to detect and overcome these biases.

Conclusion: In order to avoid bias in trial-based economic evaluations, one has to be aware of all the possible forms of bias. All stakeholders have to examine trial-based economic evaluations in a rigorous and stringent manner. This article can be helpful in this examination as it gives an overview of the possible biases which researchers should take into account.     

AN EXPERIENTIALLY DERIVED BASE-RATE ERROR IN HUMANS

Abstract— Two experiments tested college students in a delayed matching-to-sample procedure designed to explore how multiple competitive sources of control interact in determining choice behavior. The primary sources of potential control were the frequency with which each of two colors was correct (base rates) and the accuracy of a sample in predicting the correct choice (accuracy rate). In one experiment, subjects ignored the base rates, and therefore made nonoptimal choices. These results mimicked the well-known base-rate error found in verbal responses to questions. In a second experiment, manipulations to increase subjects' motivation did not alleviate the error significantly. Together, these results suggest that the base-rate error may represent a broad behavioral pattern not restricted to verbal arenas. The results are compared with previous attempts to reconcile behavioral and cognitive lines of experimentation.     

Callous-unemotional traits and developmental pathways to severe conduct problems

One method for defining pathways through which children develop severe conduct problems is based on the presence or absence of callous-unemotional (CU) traits. This study investigated potential differences between nonreferred children (mean age = 12.36 years; SD = 1.73) with and without CU traits (n = 98). Children with conduct problems, irrespective of the presence of CU traits, tended to have significant problems in emotional and behavioral regulation. In contrast, CU traits, irespective of the presence of conduct problems, were associated with a lack of behavioral inhibition. Hostile attributional biases were associated with conduct problems but only in boys and in the absence of CU traits. These findings suggest that the processes underlying deficits in emotional and behavioral regulation in children with conduct problems may be different for children with CU traits.     

Forebrain circuits and control of feeding by learned cues

Professor Richard F. Thompson and his highly influential work on the brain substrates of associative learning and memory have critically shaped my research interests and scientific approach. I am tremendously grateful and thank Professor Thompson for the support and influence on my research and career. The focus of my research program is on associative learning and its role in the control of fundamental, motivated behaviors. My long-term research goal is to understand how learning enables environmental cues to control feeding behavior. We use a combination of behavioral studies and neural systems analysis approach in two well-defined rodent models to study how learned cues are integrated with homeostatic signals within functional forebrain networks, and how these networks are modulated by experience. Here, I will provide an overview of the two behavioral models and the critical neural network components mapped thus far, which include areas in the forebrain, the amygdala and prefrontal cortex, critical for associative learning and decision-making, and the lateral hypothalamus, which is an integrator for feeding, reward and motivation.     

To adjust or not adjust: Nonparametric effect sizes,confidence intervals,and real-world meaning

ObjectivesThe main objectives of this article are to: (a) investigate if there are any meaningful differences between adjusted and unadjusted effect sizes (b) compare the outcomes from parametric and non-parametric effect sizes to determine if the potential differences might influence the interpretation of results, (c) discuss the importance of reporting confidence intervals in research, and discuss how to interpret effect sizes in terms of practical real-world meaning.DesignReview.MethodA review of how to estimate and interpret various effect sizes was conducted. Hypothetical examples were then used to exemplify the issues stated in the objectives.ResultsThe results from the hypothetical research designs showed that: (a) there is a substantial difference between adjusted and non-adjusted effect sizes especially in studies with small sample sizes, and (b) there are differences in outcomes between the parametric and non-parametric effect size formulas that may affect interpretations of results.ConclusionsThe different hypothetical examples in this article clearly demonstrate the importance of treating data in ways that minimize potential biases and the central issues of how to discuss the meaningfulness of effect sizes in research.