An important aspect of causal inference is assessing the contingency between antecedents and
outcomes. Research on how people integrate contingency information has focused on identifying
the "best" rule to descriptively model the information integration process. In contrast to this ruleanalytic
approach, the present feature-analytic approach asks the question, "What features are
important in describing the information integration process?" Five key propositions of the present
account are that (a) people prefer strategies that involve contrasting data with conflicting
implications to strategies that involve seeking only confirmatory or marginal-frequency data, (b)
people weigh positive information more heavily than negative information, (c) people are biased
toward testing sufficiency rather than necessity, (d) people are biased toward strategies that
cohere with the perceived direction of time (input tests) rather than those that violate this
perception (outcome tests), and (e) people are biased toward probability strategies that enable
comparability across data contexts rather than frequency strategies that do not. In three
experiments, subjects received contingency information on two, temporally sequenced, binary
variables in numeric summary format. Subjects were asked to rate the direction and magnitude of
the causal relation between the two variables based on the contingency information provided.
Results of Experiments 1-3, corroborated by a reanalysis of data from two published experiments
employing a discrete-trial method for presenting stimuli, strongly supported the first four
propositions. To test the fifth proposition, I reanalyzed data from five published experiments in
addition to an analysis of data from Experiment 3. Results indicated that within each data context
preferences for either frequency, conditional-probability, or joint-probability strategies emerged,
but across contexts consistent preferences for one type of combination method was lacking.
Taken together, the findings indicate that invariant properties of the information integration
process in causal inference can be isolated but these consist of systematic feature preferences
rather than stable rankings of rules in terms of their predictive utility. / Arts, Faculty of / Psychology, Department of / Graduate
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/6201 |
| Date | 11 1900 |
| Creators | Mandel, David R. |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Format | 5355554 bytes, application/pdf |
| Rights | For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use. |
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