Causal beliefs and conditioned responses: Retrospective revaluation induced by experience and by instruction.

The author tested causal beliefs and conditioned responses in a task involving retrospective revaluation of the causal status of a target cue with respect to electric shock. Successful revaluation was observed on both self-report shock expectancy and skin conductance, whether the training trials were directly experienced, described, or partly experienced and partly described. The results contradict models that link anticipatory conditioned responses to a separate or earlier process from that underlying explicit causal knowledge. They suggest instead that a single learning process gives rise to propositional knowledge that (a) drives anticipatory responding, (b) forms the basis for self-reported causal beliefs, and (c) can be combined with other knowledge, provided either by experience or symbolically, to generate inferences such as retrospective revaluation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Retrospective revaluation of causal judgments under positive and negative contingencies.

Retrospective revaluation of causal judgments was investigated in a 2-stage procedure. In the 1st stage, compounds of 2 cues were associated with the outcome, whereas in the 2nd stage, a cue from each compound was trained by itself. Associating this cue with the outcome in the 2nd stage had no detectable effect on the causal rating of the other cue from the compound, whereas presenting it without the outcome enhanced the causal rating of the other cue. The retrospective revaluation of the causal rating of these productive cues and also of preventative cues depended on consistent pairing of the cues during compound training, suggesting a role for within-compound associations. These results favor associative accounts of retrospective revaluation that use separate excitatory and inhibitory learning processes rather than a general error-correcting learning algorithm. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Inference-based retrospective revaluation in human causal judgments requires knowledge of within-compound relationships.

In an allergist causal-judgment task, food compounds were followed by an allergic reaction (e.g., AB+), and then 1 cue (A) was revalued. Experiment 1, in which participants who were instructed that whatever was true about one element of a causal compound was also true of the other, showed a reverse of the standard retrospective revaluation effect. That is, ratings of B were higher when A was causal (A+) than when A was safe (A-). This effect was taken to reflect inferential reasoning, not an associative mechanism. In Experiment 2, within-compound associations were found to be necessary to produce this inference-based revaluation. Therefore, evidence that within-compound associations are necessary for retrospective revaluation is consistent with the inferential account of causal judgments. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The priority of just-identified, recursive models.

Theories often place constraints on causal relationships, and such constraints are often assessed with causal models. Causal models should be recursive and just identified because cause is recursive and is more likely to be just identified than overidentified. A just-identified, recursive model (JIRM) is specified that satisfies both requirements and that can be used to assess a wide range of causal implications in either a norm-referenced or criterion-referenced manner. P. E. Meehl and N. G. Waller (2002) proposed an innovative method for theory appraisal called the delete one-add one (D1 -A1) method, which assesses a relatively narrow range of causal implications, allows nonrecursive models, and is only norm referenced. The JIRM and D1-A1 methods are compared. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Conditioned inhibition produced by extinction-mediated recovery from the relative stimulus validity effect: A test of acquisition and performance models of empirical retrospective revaluation.

Empirical retrospective revaluation is a phenomenon of Pavlovian conditioning and human causal judgment in which posttraining changes in the conditioned response (Pavlovian task) or causal rating (causal judgment task) of a cue occurs in the absence of further training with that cue. Two experiments tested the contrasting predictions made by 2 families of models concerning retrospective revaluation effects. In a conditioned lick-suppression task, rats were given relative stimulus validity training, consisting of reinforcing a compound of conditioned stimuli (CSs) A and X and nonreinforcement of a compound of CSs B and X, which resulted in low conditioned responding to CS X. Massive posttraining extinction of CS A not only enhanced excitatory responding to CS X, but caused CS B to pass both summation (Experiment 1) and retardation (Experiment 2) tests for conditioned inhibition. The inhibitory status of CS B is predicted by the performance-focused extended comparator hypothesis (J. C. Denniston, H. I. Savastano, & R. R. Miller, 2001), but not by acquisition-focused models of empirical retrospective revaluation (e.g., A. Dickinson & J. Burke, 1996; L. J. Van Hamme & E. A. Wasserman, 1994). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Associative History Affects the Associative Change Undergone by Both Presented and Absent Cues in Human Causal Learning.

R. A. Rescorla (2000) noted that a number of influential theories of associative learning do not take the associative history of cues (i.e., the prior training that they have received) into account when calculating the associative change undergone by those cues. The authors tested this assumption in a human causal learning paradigm and found associative history to be an important determinant of the learning undergone by cues that are presented on a trial. Moreover, associative history was also found to influence the amount of retrospective revaluation undergone by absent cues. These findings conflict with models of causal learning in which the associative change undergone by an element of a cue compound is governed by a summed error term (e.g., R. A. Rescorla & A. R. Wagner, 1972). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

An autoassociative model of causal reasoning and causal learning: Reply to Van Overwalle's (1998) critique of Read and Marcus-Newhall (1993).

The authors respond to F. Van Overwalle's (see record 1997-38975-003) critique of the explanatory coherence (ECHO) model of causal reasoning (P. Thagard, 1992) and its application to social reasoning (S. J. Read & A. Marcus-Newhall; see record 1994-01615-001). Contrary to Van Overwalle's doubts about its possibility, a feedback model similar to ECHO that learns covariation information appropriately is presented. This model simulates Read and Marcus-Newhall's results and can also simulate findings from the causal learning literature. In contrast, because of limitations in feedforward networks, Van Overwalle can simulate many of Read and Marcus-Newhall's results only by making incorrect assumptions about their procedures. Further, the model presented handles several issues that Van Overwalle's cannot, such as asymmetries in reasoning between cause and effect, evaluation of explanatory coherence, and causal chains. Finally, limitations of feedforward models of causal reasoning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Driven by power? Probe question and presentation format effects on causal judgment.

It has been proposed that causal power (defined as the probability with which a candidate cause would produce an effect in the absence of any other background causes) can be intuitively computed from cause-effect covariation information. Estimation of power is assumed to require a special type of counterfactual probe question, worded to remove potential sources of ambiguity. The present study analyzes the adequacy of such questions to evoke normative causal power estimation. The authors report that judgments to counterfactual probes do not conform to causal power and that they strongly depend on both the probe question wording and the way that covariation information is presented. The data are parsimoniously accounted for by an alternative model of causal judgment, the Evidence Integration rule. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The influence of virtual sample size on confidence and causal-strength judgments.

The authors investigated whether confidence in causal judgments varies with virtual sample size--the frequency of cases in which the outcome is (a) absent before the introduction of a generative cause or (b) present before the introduction of a preventive cause. Participants were asked to evaluate the influence of various candidate causes on an outcome as well as to rate their confidence in those judgments. They were presented with information on the relative frequencies of the outcome given the presence and absence of various candidate causes. These relative frequencies, sample size, and the direction of the causal influence (generative vs. preventive) were manipulated. It was found that both virtual and actual sample size affected confidence. Further, confidence affected estimates of strength, but confidence and strength are dissociable. The results enable a consistent explanation of the puzzling previous finding that observed causal-strength ratings often deviated from the predictions of both of the 2 dominant models of causal strength. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A memory-based account of retrospective revaluation.

We adapt an instance model of human memory, Minerva 2, to simulate retrospective revaluation. In the account, memory preserves the events of individual trials in separate traces. A probe presented to memory contacts all traces in parallel and causes each to become active. The information retrieved from memory is the sum of the activated traces. Learning is modelled as a process of cued-recall; encoding is modelled as a process of differential encoding of unexpected features in the probe (i.e., expectancy-encoding). The model captures three examples of retrospective revaluation: backward blocking, recovery from blocking, and backward conditioned inhibition. The work integrates an understanding of human memory and complex associative learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Is causal induction based on causal power? Critique of Cheng (1997).

The authors empirically evaluate P. W. Cheng's (see record 1997-03612-007) power PC theory of causal induction. They reanalyze some published data taken to support the theory and show instead that the data are at variance with it. Then, they report 6 experiments in which participants evaluated the causal relationship between a fictitious chemical and DNA mutations. The power PC theory assumes that participants' estimates are based on the causal power p of a potential cause, where p is the contingency between the cause and the effect normalized by the base rate of the effect. Three of the experiments used a procedure in which causal information was presented trial by trial. For these experiments, the power PC theory was contrasted with the predictions of the probabilistic contrast model and the Rescorla-Wagner theory. For the remaining 3 experiments, a summary presentation format was employed to which only the probabilistic contrast model and the power PC theory are applicable. The power PC theory was unequivocally contradicted by the results obtained in these experiments, whereas the other 2 theories proved to be satisfactory. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Causal judgments about relations between multilevel variables.

Three experiments presented stimulus information about cause and effect variables taking 3 quantitative values. Judgments tended to vary in accordance with considerations of conditions affecting the validity of causal inference from correlational data: whether causal candidates were presented simultaneously or in a temporal order such that one could affect the other and whether candidates were confounded with each other. The results supported a general hypothesis that causal judgments are moderated in accordance with acquired methodological intuitions. The 4th experiment showed that tendencies in correlation judgment were different from those in causal judgment, further supporting the hypothesis that causal judgment from multilevel variable information is, to some extent, determined by processes or conceptual frameworks specific to the domain of causal cognition. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Attributional information processing: A response time model of causal subtraction.

Response time measures have been used occasionally in social psychology, but rarely as direct probes of information processing. A study (with 24 undergraduates) collecting response time data in a near-exact replication of L. McArthur's (see record 1972-27156-001) classic attribution study sheds light on the information processing involved in Ss' responses. The process is analyzed into 2 stages: (a) encoding or comprehension of the stimulus sentence and the consensus, distinctiveness, and consistency information and (b) attributional processing per se. In the 2nd stage, response time analyses suggest that perceivers operate by subtracting causes from an initial set to arrive at a response, rather than by adding causal components (person, stimulus, and circumstances) until an adequate cause is obtained. Subtraction is theoretically related to the salience model of attribution. Response time measures promise to expand greatly the ability of social psychologists to build process models of causal attribution and other kinds of social perception and cognition. (25 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Making causal judgments from the proportion of confirming instances: The pCI rule.

It is proposed that causal judgments about contingency information are derived from the proportion of confirmatory instances (pCI) that are evaluated as confirmatory for the causal candidate. In 6 experiments, pCI values were manipulated independently of objective contingencies assessed by the ΔP rule. Significant effects of the pCI manipulations were found in all cases, but causal judgments did not vary significantly with objective contingencies when pCI was held constant. The experiments used a variety of stimulus presentation procedures and different dependent measures. The power PC theory, a weighted version of the ΔP rule, the Rescorla-Wagner associative learning model (R. A. Rescorla & A. R. Wagner, 1972), and the ΔD rule, which is the frequency-based version of the pCI rule, were unable to account for the significant effects of the pCI manipulations. These results are consistent with a general explanatory approach to causal judgment involving the evaluation of evidence and updating of beliefs with regard to causal hypotheses. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mechanisms of predictive and diagnostic causal induction.

In predictive causal inference, people reason from causes to effects, whereas in diagnostic inference, they reason from effects to causes. Independently of the causal structure of the events, the temporal structure of the information provided to a reasoner may vary (e.g., multiple events followed by a single event vs. a single event followed by multiple events). The authors report 5 experiments in which causal structure and temporal information were varied independently. Inferences were influenced by temporal structure but not by causal structure. The results are relevant to the evaluation of 2 current accounts of causal induction, the Rescorla-Wagner (R. A. Rescorla & A. R. Wagner, 1972) and causal model theories (M. R. Waldmann & K. J. Holyoak, 1992). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Selection mechanisms in reading lexically ambiguous words.

Readers' eye movements were monitored as they read sentences containing lexically ambiguous words. The ambiguous words were either biased (one strongly dominant interpretation) or nonbiased. Readers' gaze durations were longer on nonbiased than biased words when the disambiguating information followed the target word. In Experiment 1, reading times on the disambiguating word did not differ whether the disambiguation followed the target word immediately or occurred several words later. In Experiment 2, prior disambiguation eliminated the long gaze durations on nonbiased target words but resulted in long gaze durations on biased target words if the context demanded the subordinate meaning. The results indicate that successful integration of one meaning with prior context terminates the search for alternative meanings of that word. This results in selective (single meaning) access when integration of a dominant meaning is fast (due to a biasing context) and identification of a subordinate meaning is slow (a strongly biased ambiguity with low-frequency meaning). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

基于D-S证据理论—正态隶属度的岩土边坡稳定性评价

针对岩土边坡稳定性评价具有模糊性和不确定性且各评价指标存在矛盾冲突性的特点，提出了基于D-S证据理论的岩土边坡稳定性综合评价方法。首先建立识别框架，选取评价指标，运用正态隶属函数确定各等级对应的质量函数。然后基于各等级质量函数间的距离，综合考虑各指标各等级之间的相互影响程度，确定指标权重。最后运用D-S组合规则，得出岩土边坡稳定性等级。将D-S证据理论评价模型运用到广州某稀土矿山工作场地，并将该方法与可拓法在质量函数与关联度、权重确定和评价结果等方面进行比较，结果表明D-S证据理论评价模型相对合理，所得结果精度较高并且与工程实际相吻合。     

Reinstatement of causal information during reading.

An on-line word naming probe was used to test whether information presented earlier in a text, and then backgrounded by several sentences, would be reinstated when Ss were required to understand the cause of a currently processed action or event. In Exp 1, Ss named a probe word that represented an earlier-mentioned cause more quickly when it followed a causal coherence break than when it followed a neutral sentence. Exps 2 and 3 replicated this effect and examined 2 conditions that may affect the process of reinstating a cause: (1) inclusion of part of the context in which the cause was originally presented was not necessary to obtain reinstatement of the cause and (2) reinstatement of the cause was not evidenced when it had been disconfirmed earlier in the text. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Spontaneous assimilation of continuous values and temporal information in causal induction.

Existing models of causal induction primarily rely on the contingency between the presence and the absence of a causal candidate and an effect. Yet, classification of observations into these four types of covariation data may not be straightforward because (a) most causal candidates, in real life, are continuous with ambiguous, intermediate values and because (b) effects may unfold after some temporal lag, providing ambiguous contingency information. Although past studies suggested various reasons why ambiguous information may not be used during causal induction, the authors examined whether learners spontaneously use ambiguous information through a process called causal assimilation. In particular, the authors examined whether learners willingly place ambiguous observations into one of the categories relevant to the causal hypothesis, in accordance with their current causal beliefs. In Experiment 1, people's frequency estimates of contingency data reflected that information ambiguous along a continuous quantity dimension was spontaneously categorized and assimilated in a causal induction task. This assimilation process was moderated by the strength of the upheld causal hypothesis (Experiment 2), could alter the overall perception of a causal relationship (Experiment 3), and could occur over temporal sequences (Experiment 4). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Belief-Based and covariation-based cues affect causal discounting.

Examined the extent to which individuals' a priori beliefs contribute to the degree of causal discounting and how those beliefs are combined with covariation-based cues. Ss were 72 university students who made causality judgments on multiple causal candidates for a single given effect in 6 stories. Each candidate varied in terms of the degree to which it covaried with the effect and the degree to which it was a believable precursor to the observed effect. The 1st cause, was of neutral belief and was moderately contingent with the effect. The 2nd cause was either highly believable or highly unbelievable and was either less, the same, or more contingent than the 1st cause. Ss made their judgments before and after being presented with the 2nd cause. The results indicate that the degree to which a causal candidate is discounted depends not only on the degree to which an alternative cause covaries with the effect, but also on whether the alternative is a believable or unbelievable candidate. Specifically, the results show that a highly believable alternative will produce the discounted effect, even if it is a weaker covariate than the original candidate. These findings suggest the need to incorporate both belief-based and covariation-based cues into models of causal attribution. (PsycINFO Database Record (c) 2010 APA, all rights reserved)