Associative and causal reasoning accounts of causal induction: Symmetries and asymmetries in predictive and diagnostic inferences

López, Francisco J.; Cobos, Pedro L.; Caño, Antonio

doi:10.3758/bf03193371

Cited by 25 publications

(25 citation statements)

References 18 publications

(40 reference statements)

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“…Thus, the propositional model could be viewed also as a performance-based model. In any case, as a noncausally framed learning task was used, it is unlikely that causal reasoning processes were triggered in the present experiment (see López, Cobos, & Caño, 2005;Luque, et al, 2008). For this reason, the present authors are reluctant to conclude that these results are consistent or not with the propositional model of learning; simply, these models are not easily applicable in the present learning task.…”

Section: Discussioncontrasting

confidence: 67%

Backward versus Forward Blocking: Evidence for Performance-Based Models of Human Contingency Learning

Luque

Vadillo

2011

Psychol Rep

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Two types of theories are usually invoked to account for cue-interaction effects in human-contingency learning, performance-based theories, such as the comparator hypothesis and statistical models, and learning-based theories, such as associative models. Interestingly, the former models predict two important cue-interaction effects, forward and backward blocking, should affect responding in a similar manner, whereas learning-based models predict the effect of forward blocking should be larger than the effect of backward blocking. Previous experiments involved important methodological problems, and results have been contradictory. The present experiment was designed to explore potential asymmetries between forward and backward blocking. Analyses yielded similar effect sizes, thereby favoring the explanation by performance-based models.

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Section: Discussioncontrasting

confidence: 67%

Backward versus Forward Blocking: Evidence for Performance-Based Models of Human Contingency Learning

Luque

Vadillo

2011

Psychol Rep

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“…Hence, blocking effects should be less likely to occur when the cues are potential effects of the outcome than when they are potential causes of the outcome. This prediction has been verified in several studies (see Lopez, Cobos, & Caño, 2005, for a review).…”

Section: First Core Assumption: Associative Learning Effects Depend Omentioning

confidence: 71%

The propositional approach to associative learning as an alternative for association formation models

Houwer

2009

Learning & Behavior

306

312

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Associative learning effects can be defined as changes in behavior that are due to relations between events in the world. Most often, these effects are explained in terms of the formation of unqualified associations in memory. I describe an alternative theoretical explanation, according to which associative learning effects are the result of the nonautomatic generation and evaluation of propositions about relations between events. This idea is supported by many studies showing that associative learning effects are determined not only by the direct experience of events but also by prior knowledge, instructions, intervention, and deductive reasoning. Moreover, evidence supports the assumption that associative learning effects depend on nonautomatic processes. Whereas a propositional approach thus offers many new insights, questions can be raised about what the idea of association formation adds to our understanding of associative learning

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“…Causal reasoning may or may not be involved in arriving at this conclusion (F. J. López, Cobos, & Caño, 2005). Research on diagnostic reasoning examines to what extent humans engage in reasoning about underlying causal processes when they aim to arrive at a diagnostic judgment.…”

Section: Introductionmentioning

confidence: 99%

The diversity effect in diagnostic reasoning

2016

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Diagnostic reasoning draws on knowledge about effects and their potential causes. The causal-diversity effect in diagnostic reasoning normatively depends on the distribution of effects in causal structures, and thus, a psychological diversity effect could indicate whether causally structured knowledge is used in evaluating the probability of a diagnosis, if the effect were to covary with manipulations of causal structures. In four experiments, participants dealt with a quasimedical scenario presenting symptom sets (effects) that consistently suggested a specified diagnosis (cause). The probability that the diagnosis was correct had to be rated for two opposed symptom sets that differed with regard to the symptoms' positions (proximal or diverse) in the causal structure that was initially acquired. The causal structure linking the diagnosis to the symptoms and the base rate of the diagnosis were manipulated to explore whether the diagnosis was rated as more probable for diverse than for proximal symptoms when alternative causations were more plausible (e.g., because of a lower base rate of the diagnosis in question). The results replicated the causal diversity effect in diagnostic reasoning across these conditions, but no consistent effects of structure and base rate variations were observed. Diversity effects computed in causal Bayesian networks are presented, illustrating the consequences of the structure manipulations and corroborating that a diversity effect across the different experimental manipulations is normatively justified. The observed diversity effects presumably resulted from shortcut reasoning about the possibilities of alternative causation.

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Associative and causal reasoning accounts of causal induction: Symmetries and asymmetries in predictive and diagnostic inferences

Cited by 25 publications

References 18 publications

Backward versus Forward Blocking: Evidence for Performance-Based Models of Human Contingency Learning

Backward versus Forward Blocking: Evidence for Performance-Based Models of Human Contingency Learning

The propositional approach to associative learning as an alternative for association formation models

The diversity effect in diagnostic reasoning

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