Are choices based on conditional or conjunctive probabilities in a sequential risk-taking task?

In this study, we examined participants' choice behavior in a sequential risk-taking task. We were especially interested in the extent to which participants focus on the immediate next choice or consider the entire choice sequence. To do so, we inspected whether decisions were either based on conditional probabilities (e.g., being successful on the immediate next trial) or on conjunctive probabilities (of being successful several times in a row). The results of five experiments with a simplified nine-card Columbia Card Task and a CPT-model analysis show that participants' choice behavior can be described best by a mixture of the two probability types. Specifically, for their first choice, the participants relied on conditional probabilities, whereas subsequent choices were based on conjunctive probabilities. This strategy occurred across different start conditions in which more or less cards were already presented face up. Consequently, the proportion of risky choices was substantially higher when participants started from a state with some cards facing up, compared with when they arrived at that state starting from the very beginning. The results, alternative accounts, and implications are discussed.     

Interaction of data and hypotheses in probabilistic inference tasks: Rejection of the hypothesis sampling model?

The problem of whether or not data influence subjects' sampling of hypotheses about functional relations in the probabilistic inference tasks was examined. The results of the experiment show first, a considerable impact of data on subjects' hypothesis selection and second, that the subjects significantly modify their hypothesis selection from one part of the experiment to the other. Thus, there is an interaction of data and hypotheses in cue probability learning (CPL) tasks regarding the hypothesis sampling process and an execution of cognitive control over the subjects' hypothesis pool.     

Signal probability, reinforcement and signal detection.

Five pigeons were trained to detect differences in light intensity. Two stimuli, S1 and S2, differing in intensity, were arranged on the center key of a three-key chamber according to set probabilities. A peck on the center key turned on the two side keys. When S1 was presented on the center key, a peck on the left key was "correct" and when S2 was presented, a peck on the right key was "correct." Correct responses produced reinforcement and incorrect responses produced 3-second blackout. Detection performance was measured under three procedures. The first was a standard signal-detection design in which the probability of S1 was varied and the number of reinforcements obtained for correct responses to S1 was allowed to covary. In the second procedure, the probability of S1 was again varied but the distribution of reinforcements between the two choices was kept equal. In the third procedure, probability of S1 was held constant while the distribution of reinforcements was varied between the two choices. Changes in response bias were a function of variations in the relative reinforcement ratio for the choice responses and not a function of variations in the probability of stimulus presentation. Discriminability remained constant across the three procedures.     

Psychometric and information processing properties of selected response time models

This paper discusses the compatibility of some response time (RT) models with psychometric and with information processing approaches to response times. First, three psychometrically desirable properties of probabilistic models for binary data, related to the principle of specific objectivity, are adapted to the domain of RT models. One of these is the separability of item and subject parameters, and another is double monotonicity. Next, the compatibility of these psychometric properties with one very popular information processing approach, the serial-additive model, is discussed. Finally, five RT models are analyzed with respect to their compatibility with the psychometric properties, with serial-additive processing and with some alternative types of processing. It is concluded that (a) current psychometric models each satisfy one or more of the psychometric properties, but are not (easily) compatible with serial-additive processing, (b) at least one serial-additive processing model satisfies separability of item and subject parameters, and (c) RT models will more easily satisfy double monotonicity than the other two psychometric properties.     

Bias in self-evaluation: Signal probability effects

Two experiments examined apparent signal probability effects in simple verbal self-reports. After each trial of a delayed matching-to-sample task, young adults pressed either a “yes” or a “no” button to answer a computer-presented query about whether the most recent choice met a point contingency requiring both speed and accuracy. A successful matching-to-sample choice served as the “signal” in a signal-detection analysis of self-reports. Difficulty of matching to sample, and thus signal probability, was manipulated via the number of nonmatching sample and comparison stimuli. In Experiment 1, subjects exhibited a bias (log b) for reporting matching-to-sample success when success was frequent, and no bias or a bias for reporting failure when success was infrequent. Contingencies involving equal conditional probabilities of point consequences for “I succeeded” and “I failed” reports had no systematic effect on this pattern. Experiment 2 found signal probability effects to be evident regardless of whether referent-response difficulty was manipulated in different conditions or within sessions. These findings indicate that apparent signal probability effects in self-report bias that were observed in previous studies probably were not an artifact of contingencies intended to improve self-report accuracy or of the means of manipulating signal probability. The findings support an analogy between simple self-reports and psychophysical judgments and bolster the conclusion of Critchfield (1993) that signal probability effects can influence simple self-reports much as they do reports about external stimuli in psychophysical experiments.