Frequency of judgment as a context-like determinant of predictive judgments (original) (raw)
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Judgement frequency, belief revision, and serial processing of causal information
The Quarterly Journal of Experimental Psychology: Section B, 2002
The main aim of this research was to study the cognitive architecture underlying causal/covariation learning by investigating the frequency of judgement effect. Previous research has shown that decreasing the number of trials between opportunities to make a judgement in a covariation learning task led to a higher score after an a or d type of trial (positive cases) than after b and c trials (negative cases). Experiment 1 replicated this effect using a trial-by-tria l procedure and examined the conditions under which it occurs. Experiment 2 demonstrated a similar frequency of judgement effect when the information was presented in the form of contingency tables. Associative or statistical single-mechanism accounts of causal and covariation learning do not provide a satisfactory explanation for these findings. An alternative belief revision model is presented.
Contextual Influences on Judgment Based on Limited Information
Organizational Behavior and Human Decision Processes, 1997
Judgment often requires the gathering, assessment, When judging objects described by incomplete eviand integration of multiple pieces of information. Perdence, people often make judgments on the basis of haps more often than not, the information that is availwhat is known and fail to adjust for what is unknown. able for these types of judgments is limited or incom-However, contextual factors may increase sensitivity to plete. Consequently, most information integration the limited weight of the given information. Consistent judgments must be made without complete knowledge with this hypothesis, four experiments show that sensiof all the relevant attributes or qualities. Thus, cars tivity to the limitations of the evidence and the likeliare assessed without knowledge of the warranty and hood of judgmental moderation increases when (a) a repair record, and academic job candidates similarly target is judged in the context of a similar object described on dimensions different from those used to de-are evaluated in the absence of information about adscribe the target, or (b) a target is judged in the context ministrative and supervisory skills. of a completely different type of object described by a According to a number of theorists (e.g., Ajzen & relatively large amount of information. Considered to-Fishbein, 1980; Anderson, 1981, 1982; von Neumann & gether, the results suggest that judgment is moderated Morgenstern, 1947), information integration judgwhen contextual objects or cues alert judges to specific ments are an additive or averaging function of the evalomissions or when contextual cues imply a general lack uative implications and weights of the information of information. The findings illuminate the diverse efabout a target. Knowledge of the value and the imporfects that even context objects of a different category tance or diagnosticity of each of the known attributes have on information integration judgment. Context obis integrated to form an overall judgment. In many jects may affect the weighting as well as the valuation instances, information integration judgments are adof the evidence about targets described by limited information and thereby contribute to judgmental modera-justed for the amount or set size of the evidence that tion. Finally, the findings illustrate the contextually is available. Demonstrations of the "set size effect" have sensitive nature of the weighting criteria that guide inshown that when information about important attriformation integration. ᭧ 1997 Academic Press butes is missing, the overall judgment of an object or issue is often moderated. Evaluations become less extreme as the amount of information described de-The authors thank Rachel Barnes and Randon Stasney for their creases, even when the value (the evaluative implicaassistance in the collection of the data. This research was supported tions) of each piece of information is held constant
Contrasting cue-density effects in causal and prediction judgments
Many theories of contingency learning assume (either explicitly or implicitly) that predicting whether an outcome will occur should be easier than making a causal judgment. Previous research suggests that outcome predictions would depart from normative standards less often than causal judgments, which is consistent with the idea that the latter are based on more numerous and complex processes. However, only indirect evidence exists for this view. The experiment presented here specifically addresses this issue by allowing for a fair comparison of causal judgments and outcome predictions, both collected at the same stage with identical rating scales. Cue density, a parameter known to affect judgments, is manipulated in a contingency learning paradigm. The results show that, if anything, the cue-density bias is stronger in outcome predictions than in causal judgments. These results contradict key assumptions of many influential theories of contingency learning
How temporal assumptions influence causal judgments
Memory & Cognition, 2002
Causal learning typically entails the problem of being confronted with a large number of potentially relevant statistical relations. One type of constraint that may guide the choice of appropriate statistical indicators of causality are assumptions about temporal delays between causes and effects. There have been a few previous studies in which the role of temporal relations in the learning of events that are experienced in real time have been investigated. However, human causal reasoning may also be based on verbally described events, rather than on direct experiences of the events to which the descriptions refer. The aim of this paper is to investigate whether assumptions about the temporal characteristics of the events that are being described also affect causal judgment. Three experiments are presented that demonstrate that different temporal assumptions about causal delays may lead to dramatically different causal judgments, despite identical learning inputs. In particular, the experiments show that temporal assumptions guide the choice of appropriate statistical indicators of causality by structuring the event stream (Experiment 1), by selecting the potential causes among a set of competing candidates (Experiment 2), and by influencing the level of aggregation of events (Experiment 3).
Judgment frequency effects in generative and preventive causal learning
2004
The frequency of judgment effect is a special case of Response Mode effect in human covariation and causal learning. Judgment adjustment -to DP-, depends on the trial type preceding that judgment, but that effect is restricted to situations in which participants are asked to make their judgments with a high frequency. Two experiments further demonstrated the reliability and the generality of this effect in positive and negative causal learning tasks. Experiment 1 yielded similar judgment frequency effects with a higher positive contingency (DP= 0.71) and a larger block size (n=16) than in previous studies. Experiment 2 showed that judgment frequency also modulates the detection of negative contingency (DP= -0.5), as far as judgment accuracy was shown to be a function of the type of trial just preceding that judgment in the high frequency group. Associative and statistical models of covariation learning cannot easily explain these results without incorporating relevant post-hoc assumptions. These findings add new-evidence to the growing body of data showing that human causal learning depends on the action of several mechanisms, as proposed by the Belief Revision Model.
Momentary and integrative response strategies in causal judgment
Memory & Cognition, 2002
Associative models of causal learning predict recency effects: Judgments at the end of a trial series should be strongly biased by recently presented information. Prior research, however, presents a contrasting picture of human performance. López, Shanks, Almaraz, and Fernández (1998) observed recency, whereas Dennis and Ahn (2001) found the opposite, primacy. Here we replicate both of these effects and provide an explanation for this paradox. Four experiments show that the effect of trial order on judgments is a function of judgment frequency, where incremental judgments lead to recency while single final judgments abolish recency and lead instead to integration of information across trials (i.e., primacy). These results challenge almost all existing accounts of causal judgment. We propose a modified associative account in which participants can base their causal judgments either on current associative strength (momentary strategy) or on the cumulative change in associative strength since the previous judgment (integrative strategy).
An enormous amount of research has been conducted that documents judgment and decision-making biases when dealing with situations involving uncertainty. The results of these experiments are generally taken as evidence that people have weaknesses when they reason about situations requiring the application of probabilistic or statistical concepts. One such paper documented that when asked to explain why events occurred, people rated a conjunction of two explanations as being more likely to have influenced the outcome than the explanations' individual components, a statistical impossibility given that a conjunction of two events cannot be more likely than their individual component events (Leddo, Abelson and Gross, 1984). The present research explores the hypothesis that the nature of the task that people are asked to perform may also contribute to the biases observed in these experiments. Here, high school participants were asked to rate the probability of both individual and conjoint explanations as in Leddo et al. (1984). However, other participants were given the same scenarios and asked to state the probability that individual or conjoint events were either true (inference) or likely to happen (prediction). Results confirmed the hypothesis that conjunction effects (rating two events as more probable than one) were strongest in explanations and weakest in predictions. This suggests that the task a person is asked to perform may contribute to whether or not people show biases in judgment and decision making.
Cue interaction and judgments of causality: Contributions of causal and associative processes
Memory & Cognition, 2004
In four experiments, the predictions made by causal model theory and the Rescorla-Wagner model were tested by using a cue interaction paradigm that measures the relative response to a given event based on the influence or salience of an alternative event. Experiments 1 and 2 uncorrelated two variables that have typically been confounded in the literature (causal order and the number of cues and outcomes) and demonstrated that overall contingency judgments are influenced by the causal structure of the events. Experiment 3 showed that trial-by-trial prediction responses, a second measure of causal assessment, were not influenced by the causal structure of the described events. Experiment 4 revealed that participants became less sensitive to the influence of the causal structure in both their ratings and their predictions as trials progressed. Thus, two experiments provided evidence for highlevel (causal reasoning) processes, and two experiments provided evidence for low-level (associative) processes. We argue that both factors influence causal assessment, depending on what is being asked about the events and participants’ experience with those events.
Effects of wording and stimulus format on the use of contingency information in causal judgment
Memory & Cognition, 2003
There are four kinds of contingency information: occurrences and nonoccurrences of an effect in the presence and in the absence of a cause. Previous studies have shown that these four kinds are not given equal weight in causal judgment. The present research was designed to test two hypotheses about this unequal weighting: that weightings are influenced by the form of the question and other features of the stimulus materials and that unequal weightings occur, in part, because individual differences in the use of contingency information are not evenly distributed across the four kinds of information. Support was found for both hypotheses. However, the effects of question wording were not always as had been predicted, indicating that more needs to be learned about how people interpret the task, instructions, and materials they are given.