A random walk model of digit comparison

Poltrock, Steven E.

doi:10.1016/0022-2496(89)90027-8

Cited by 31 publications

(58 citation statements)

References 12 publications

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“…A subject can perceive, from experience with previous trials, that a small standard is likely to be followed by a larger comparison. When this bias is taken into account, a much better lit of the data to the predictions of this theory are obtained, not only in this case, but also in results reported by Poltrock (1989 Mean response times for "Larger" and for "Smaller" responses and the proportion of "Larger" responses (scaled on the righthand ordinate).…”

Section: Corroborative Investigations: Experiments 1 Andmentioning

confidence: 66%

Modeling imageless thought: The relative judgment theory of numerical comparisons

Link

1990

Journal of Mathematical Psychology

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Section: Corroborative Investigations: Experiments 1 Andmentioning

confidence: 66%

Modeling imageless thought: The relative judgment theory of numerical comparisons

Link

1990

Journal of Mathematical Psychology

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“…Such a notion actually receives some empirical support here from the fact that the RT differences in Experiment 4 for responding to the two different stimulus sets were significantly larger when confidence was required than when it was not (note also that an analogous marginally significant effect occurred in both Experiments 2 and 3). In general, it can be demonstrated (e.g., Poltrock, 1989) that decision-related RT effects are typically more exaggerated under accuracy than under speed sets (an effect that follows naturally from the assumption that participants wait to accrue more evidence under an accuracy set).…”

Section: Discussionmentioning

confidence: 99%

Selective attention and subjective confidence calibration

Schoenherr

Leth‐Steensen

Petrusic

2010

Attention, Perception, & Psychophysics

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Selective AttentionOne paradigm that has been widely used to observe constraints on selective visual attention processing involves B. A. Eriksen and C. W. Eriksen's (1974) In the present experiments, failures of selective visual attention were invoked using the B. A. Eriksen and C. W. Eriksen (1974) flanker task. On each trial, a three-letter stimulus array was flashed briefly, followed by a mask. The identity of the two flanking letters was response congruent, neutral, or incongruent with the identity of the middle target letter. On half of the trials, confidence ratings were obtained after each response. In the first three experiments, participants were highly overconfident in the accuracy of their responding to incongruent flanker stimulus arrays. In a final experiment, presenting a prestimulus target location cue greatly reduced both selective attention failure and overconfidence. The findings demonstrate that participants are often unaware of such selective attention failures and provide support for the notion that, in these cases, decisional processing is driven largely by the identities of the incongruent flankers. In addition, responding was invariably slower and sometimes more accurate when confidence was required than when it was not required, demonstrating that the need to provide posttrial confidence reports can affect decisional processing. Moreover, there was some evidence that the presence of neutral contextual flanking information can slow responding, suggesting that such nondiagnostic information can, indeed, contribute to decisional processing.

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“…It may be possible to construct an architecture change theory that yields a sufficiently small shape effect, so as not to be contradicted by the present analysis. Symbolic distance is not typically modeled as an architecture change; instead, it is modeled as a diffusion process or random walk (e.g., Link, 1990;Poltrock, 1989;Schwarz, 2001;Smith & Mewhort, 1998). Changes in scale are broadly consistent with either a change in drift rate or a change in bounds.…”

Section: Discussionmentioning

confidence: 99%

“…In the experimental task, participants decide whether a presented digit is greater than or less than 5. In this task, it typically takes longer to make decisions about digits close to 5, such as 6 and 4, than to digits far from 5, such as 2 and 8 (Link, 1990;Moyer & Landauer, 1967;Poltrock, 1989;Smith & Mewhort, 1998). The interpretation typically offered is that when performing this task, participants represent numbers in an analogue fashion (Moyer & Landauer, 1967).…”

Section: An Application To a Symbolic Distance Effectmentioning

confidence: 99%

A hierarchical model for estimating response time distributions

Rouder

Speckman

et al. 2005

Psychonomic Bulletin & Review

170

191

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We present a statistical model for inference with response time (RT) distributions. The model has the following features. First, it provides a means of estimating the shape, scale, and location (shift) of RT distributions. Second, it is hierarchical and models between-subjects and within-subjects variability simultaneously. Third, inference with the model is Bayesian and provides a principled and efficient means of pooling information across disparate data from different individuals. Because the model efficiently pools information across individuals, it is particularly well suited for those common cases in which the researcher collects a limited number of observations from several participants. Monte Carlo simulations reveal that the hierarchical Bayesian model provides more accurate estimates than several popular competitors do. We illustrate the model by providing an analysis of the symbolic distance effect in which participants can more quickly ascertain the relationship between nonadjacent digits than that between adjacent digits. THEORETICAL AND REVIEW ARTICLES

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A random walk model of digit comparison

Cited by 31 publications

References 12 publications

Modeling imageless thought: The relative judgment theory of numerical comparisons

Modeling imageless thought: The relative judgment theory of numerical comparisons

Selective attention and subjective confidence calibration

A hierarchical model for estimating response time distributions

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