Causal inferences as perceptual judgments

We analyze how subjects make causal judgments based on contingency information in two paradigms. In the discrete paradigm, subjects are given specific information about the frequency a, with which a purported cause occurs with the effect; the frequency b, with which it occurs without the effect; the frequency c, with which the effect occurs when the cause is absent; and the frequency d, with which both cause and effect are absent. Subjects respond toP ₁ =a/(a+b) andP ₂ =c/(c+d). Some subjects’ ratings are just a function ofP ₁, while others are a function of ΔP =P ₁ -P ₂. Subjects’ postexperiment reports are accurate reflections of which model they use. Combining these two types of subjects results in data well fit by the weighted ΔP model (Allan, 1993). In the continuous paradigm, subjects control the purported causes (by clicking a mouse) and observe whether an effect occurs. Because causes and effects occur continuously in time, it is not possible to explicitly pair causes and effects. Rather, subjects report that they are responding to the rate at which the effects occur when they click versus when they do not click. Their ratings are a function of rates and not probabilities. In general, we argue that subjects’ causal ratings are judgments of the magnitude of perceptually salient variables in the experiment.     

Causal uncertainty and correction of judgments

We examined whether raising uncertainty about the causes of one’s judgments motivates correction. Specifically, we examined whether activating chronically accessible causal uncertainty (CU) beliefs with a conditional warning about possible bias enhances correction of weather judgments for tropical weather primes and of word frequency judgments for the availability bias. In two studies we showed that activating chronic beliefs led to careful correction of target judgments. Moreover, Study 2 revealed that chronically high-CU individuals who received a conditional warning felt more uncertain than did other participants, but that this uncertainty was suppressed somewhat by adjusting for the bias. Results are discussed in light of recent models of judgment correction (e.g., Wegener & Petty, 1997), and the causal uncertainty model (Weary & Edwards, 1996).     

Social judgments of spurious and causal relations between attributes and outcomes

People can learn about relations between attributes and outcomes by observing the attributes and outcomes of others, but, as this experiment indicates, such learning is not always veridical. Each subject received information about the ages, educations, and salaries of groups of employees in a fictitious corporation. Within a group, either age or education was related to salaries and the two attributes were either orthogonal or correlated. In each case, subjects judged the strength of the causal relation between each attribute and salaries. The results confirmed our hypothesis that observers are more likely to view a causally relevant attribute as irrelevant, and a causally irrelevant attribute as relevant, when relevant and irrelevant attributes are correlated. However, this tendency seemed to be mediated by subjects' bias to prefer education as an explanation of salary differences: That is, when age and education were correlated, subjects tended to view education as relevant even when it was irrelevant and age as irrelevant even when it was relevant. The results suggest that when attributes are correlated, factors extraneous to observed data may have a major influence on inferred attribute-outcome associations.     

Causal attribution and dispositional inference: Evidence of inconsistent judgments

Two experiments examined whether individuals who ascribe the disparity in the performances of two actors to situational constraints adequately adjust their dispositional inferences to reflect their own perceptions of causality. Using the quiz-game format of L. D. Ross, T. M. Amabile, and J. L. Steinmetz (1977, Journal of Personality and Social Psychology, 35, 485–494), the effects of the subjects' awareness of the role-determined, self-presentation advantage of the questioner on their dispositional inferences concerning the quiz-game participants are noted. It is hypothesized that subjects who indicated full awareness of the determining force of the situation would nevertheless draw more favorable dispositional inferences about the questioner than about the contestant. The prediction is confirmed. Although the situationally aware subjects rate the questioner and contestant more similarly than do the other subjects, they still rate the questioner higher in knowledge, memory, and education. The results of Experiment 2 indicate that increasing the salience of the subjects' assessment of the situational advantage of the questioner does not eliminate the disparity. It is proposed that the fudamental attribution error represents more a failure to adjust trait inferences for causal attributions than a misperception of causality. Implications concerning the relationship between knowledge of causality and social judgment and the utility of the distinction between “perceived causality” and “higher order causal inferences” are discussed.     

A developmental dissociation between category and function judgments about novel artifacts

Two studies investigated the relative importance of information about intended design and current use on judgments about the function (Experiment 1) or category (Experiment 2) of novel artifacts in preschool children and adults. Adults assigned function and name on the basis of information about design across all conditions, while children’s decisions about function dissociated from decisions about category. Function judgments (in both 4 and 6-year-olds) were neutral between design and current use, both when the current use was idiosyncratic (e.g. performed by just one agent) and conventional (performed by many people; Experiment 1). By contrast, where category judgments were required for the very same objects (Experiment 2), children named according to design intentions - but only if the alternate function was idiosyncratic. Judging function and assigning category are thus cognitive tasks that draw on different information across development, a fact that should be captured by theories of developing artifact concept structure.     

Perceived causal relations: novel methodology for assessing client attributions about causal associations between variables including symptoms and functional impairment

Researchers have argued that the investigation of causal interrelationships between symptoms may help explain the high comorbidity rate between certain psychiatric disorders. Clients' own attributions concerning the causal interrelationships linking the co-occurrence of their symptoms represent data that may inform their clinical case conceptualization, treatment, and psychological theory regarding the etiology of comorbid disorders. The present study developed and evaluated a novel psychological assessment methodology for measuring Perceived Causal Relations (PCR) and examined its psychometric properties as applied to the question of whether posttraumatic stress and anxiety symptoms represent causal risk factors for depressive symptoms in 225 undergraduates. Participants attributed their symptoms of anxiety and posttraumatic reexperiencing as significant causes of their depressive symptoms. Exploratory analyses identified a listing of symptoms reliably attributed as significant causes of other symptoms and functional impairment, as well as a listing of symptoms reliably attributed as significant effects (outcomes) of other symptoms and functional impairment. The PCR method has promise as an idiographic approach to assessing the causes and consequences of comorbid psychiatric symptoms and associated functional impairment. Research is required to assess the relevance and replicate these findings in distinct psychiatric groups experiencing various symptomatic presentations. Future research may also examine PCR ratings associating other individual differences, for example, between measures of history (e.g., life events), life choices, and personality.     

Fundamental dimensions of social judgment: understanding the relations between judgments of competence and warmth

In seems there are two dimensions that underlie most judgments of traits, people, groups, and cultures. Although the definitions vary, the first makes reference to attributes such as competence, agency, and individualism, and the second to warmth, communality, and collectivism. But the relationship between the two dimensions seems unclear. In trait and person judgment, they are often positively related; in group and cultural stereotypes, they are often negatively related. The authors report 4 studies that examine the dynamic relationship between these two dimensions, experimentally manipulating the location of a target of judgment on one and examining the consequences for the other. In general, the authors' data suggest a negative dynamic relationship between the two, moderated by factors the impact of which they explore.     

Linear relations amongk sets of variables

A family of solutions for linear relations amongk sets of variables is proposed. It is shown how these solutions apply fork=2, and how they can be generalized from there tok3.The family of solutions depends on three independent choices: (i) to what extent a solution may be influenced by differences in variances of components within each set; (ii) to what extent the sets may be differentially weighted with respect to their contribution to the solution—including orthogonality constraints; (iii) whether or not individual sets of variables may be replaced by an orthogonal and unit normalized basis.Solutions are compared with respect to their optimality properties. For each solution the appropriate stationary equations are given. For one example it is shown how the determinantal equation of the stationary equations can be interpreted.     

Causal relations and feature similarity in children's inductive reasoning

Four experiments examined the development of property induction on the basis of causal relations. In the first 2 studies, 5-year-olds, 8-year-olds, and adults were presented with triads in which a target instance was equally similar to 2 inductive bases but shared a causal antecedent feature with 1 of them. All 3 age groups used causal relations as a basis for property induction, although the proportion of causal inferences increased with age. Subsequent experiments pitted causal relations against featural similarity in induction. It was found that adults and 8-year-olds, but not 5-year-olds, preferred shared causal relations over strong featural similarity as a basis for induction. The implications for models of inductive reasoning and development are discussed.     

Self-serving judgments about winning the lottery

Although myths and stereotypes about lottery winners tend to be negative (e.g., winners become extravagant), people continue to spend billions of dollars buying lottery tickets in the hope of winning. The authors applied findings from the self-enhancement literature to understand this paradox. Eighty college students received class credit for their participation, in which they read a scenario that asked them to imagine that they, or a target other, had won a lottery. Participants' responses to a 34-item questionnaire displayed a self-serving bias, such that changes to the self were expected to be more positive than changes to the other. For several items, this effect was moderated by the participant's gender. The present research indicates that the pervasive tendency to display self-serving biases can apply to future-oriented processing, an under-researched topic.     

Reasoning about relations

Inferences about spatial, temporal, and other relations are ubiquitous. This article presents a novel model-based theory of such reasoning. The theory depends on 5 principles. (a) The structure of mental models is iconic as far as possible. (b) The logical consequences of relations emerge from models constructed from the meanings of the relations and from knowledge. (c) Individuals tend to construct only a single, typical model. (d) They spontaneously develop their own strategies for relational reasoning. (e) Regardless of strategy, the difficulty of an inference depends on the process of integration of the information from separate premises, the number of entities that have to be integrated to form a model, and the depth of the relation. The article describes computer implementations of the theory and presents experimental results corroborating its main principle.     

Causal learning about tolerance and sensitization

We introduce two abstract, causal schemata used during causal learning. (1) Tolerance is when an effect diminishes over time, as an entity is repeatedly exposed to the cause (e.g., a person becoming tolerant to caffeine). (2) Sensitization is when an effect intensifies over time, as an entity is repeatedly exposed to the cause (e.g., an antidepressant becoming more effective through repeated use). In Experiment 1, participants observed either of these cause—effect data patterns unfolding over time and exhibiting the tolerance or sensitization schemata. Participants inferred stronger causal efficacy and made more confident and more extreme predictions about novel cases than in a condition with the same data appearing in a random order over time. In Experiment 2, the same tolerance/sensitization scenarios occurred either within one entity or across many entities. In the manyentity conditions, when the schemata were violated, participants made much weaker inferences. Implications for causal learning are discussed.     

Judgments about judgments: the dissociation of consideration price and transaction commitment judgments

There are many contexts in which people make judgments about prior judgments. For example, Internet shopping bots (e.g., NexTag.com) allow consumers to search for products and, if the price is too high, list a price at which they would consider making the purchase (i.e., base judgment). If the price drops to this level, the vendor generates an e-mail inviting the consumer to execute the transaction at the reduced price (i.e., contingent judgment). The authors show that the consideration price depends on the content of retrieved information, whereas the willingness to execute the transaction at the consideration price depends on the ease-of-retrieving the information. The authors use different offer prices to encourage the consumer to retrieve information consistent with different product quality levels. The authors also select offer prices so that information retrieval is more difficult at moderate offer prices than at high or low offer prices. Accordingly, the authors show that the consideration price increases as the offer price increases, but the willingness to execute the transaction at the consideration price is greater when there are high and low, as opposed to moderate, offer prices.     

Six-year-olds' contradictory judgments about knowledge and beliefs

By around the age of 4 years, children acknowledge that people can have false beliefs about the world. Six-year-olds are still inclined, however, to confuse their own knowledge with that of more ignorant others. In a recent paper, Hulme, Mitchell and Wood offer a novel explanation for six-year-olds' tendency to make such errors when asked to choose a picture to put in a story character's thought bubble.     

Causal Warrant for Realism about Particle Physics

While scientific realism generally assumes that successful scientific explanations yield information about reality, realists also have to admit that not all information acquired in this way is equally well warranted. Some versions of scientific realism do this by saying that explanatory posits with which we have established some kind of causal contact are better warranted than those that merely appear in theoretical hypotheses. I first explicate this distinction by considering some general criteria that permit us to distinguish causal warrant from theoretical warrant. I then apply these criteria to a specific case from particle physics, claiming that scientific realism has to incorporate the distinction between causal and theoretical warrant if it is to be an adequate stance in the philosophy of particle physics.     

Causal judgement from information about outcome magnitude

Information was presented in which a candidate cause was either present or absent, and the outcome variable (number of spots on a patient's skin) could take any of four nonzero values. It was found that cause-absent information carried greater weight than cause-present information. This is contrary to the usual finding for contingency information about binary outcome variables. Judgement was influenced more by extreme values of the outcome variable, and larger outcome values tended to have more effect on judgements than smaller outcome values. The hypothesis that participants compute linear correlation is disconfirmed by these results. Instead, the results show that participants focus disproportionate attention on some kinds of events and neglect others.     

Causal relations drive young children's induction, naming, and categorization

A number of recent models and experiments have suggested that evidence of early category-based induction is an artifact of perceptual cues provided by experimenters. We tested these accounts against the prediction that different relations (causal versus non-causal) determine the types of perceptual similarity by which children generalize. Young children were asked to label, to infer novel properties, and to project future appearances of a novel animal that varied in two opposite respects: (1) how much it looked like another animal whose name and properties were known, and (2) how much its parents looked like parents of another animal whose name and properties were known. When exemplar origins were known, children generalized to exemplars with similar origins rather than with similar appearances; when origins were unknown, children generalized to exemplars with similar appearances. Results indicate even young children possess the cognitive control to choose the similarities that best predict accurate generalizations.