The belief-bias effect in formal reasoning: The influence of knowledge on logic

Revlin, Russell; Leirer, Von O.; Yopp, Hallie Kay; Yopp, R.

doi:10.3758/bf03213778

Cited by 153 publications

(45 citation statements)

References 25 publications

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“…The belief-bias effect refers to the tendency to accept a conclusion that accords with one's belief, regardless of whether that conclusion is in fact valid. This effect has been widely replicated (e.g., Cherubini et al, 1998;Evans et al, 1983;Evans, Newstead, Allen, & Pollard, 1994;Evans & Pollard, 1990;Feather, 1964;Janis & Frick, 1943;Markovits & BouffardBouchard, 1992;Markovits & Nantel, 1989;Morgan & Morton, 1944;Newstead et al, 1992;Oakhill & Johnson-Laird, 1985;Oakhill, Johnson-Laird & Garnham, 1989;Revlin et al, 1980;Stanovich & West, 1997;Thompson, 1996;Torrens, Thompson, & Cramer, 1999). In contrast to the rather pessimistic view of human rationality suggested by the belief-bias effect, however, it has also been widely observed that reasoners accept more valid than invalid conclusions, regardless of believability (Evans et al, 1983;Evans et al, 1994;Newstead et al, 1992;Thompson, 1994Thompson, , 1996Torrens et al, 1999).…”

Section: Beliefs and Validity In Deductive Reasoningmentioning

confidence: 71%

“…As mentioned earlier, the default method is a within-subjects design whereby reasoners are asked to complete a large number of very similar reasoning problems. A quick review of several recent belief-bias studies (Cherubini et al, 1998;Evans et al, 1983;Evans et al, 1994;Evans & Pollard, 1990;Markovits & BouffardBouchard, 1992;Markovits & Nantel, 1989;Newstead et al, 1992;Oakhill & JohnsonLaird, 1985;Oakhill et al, 1989;Revlin et al, 1980;Stanovich & West, 1997;Thompson, 1996;Torrens et al, 1999) indicated that the median number of problems reasoners are asked to solve is 8 (mean=9) ; typically, reasoners are asked to solve some multiple of four (allowing one problem in each belief by validity cell) or six problems (when a neutral belief condition is included).…”

Section: The Relative Merits Of Within-and Between-subjects Designsmentioning

confidence: 99%

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A Power Struggle: Between- Vs. Within-Subjects Designs in Deductive Reasoning Research

Thompson

Campbell

2004

PSYCHOLOGIA -An International Journal of Psychological Sciences

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This experiment examined the relative merits of using within-and between-subjects designs to investigate deductive reasoning. Two issues were investigated: 1) the potential for expectancy and fatigue effects when using within-subjects designs, and 2) the relative power of within-vs between-subjects designs. Participants were presented with problems in a standard belief-bias paradigm in which the believability of putative conclusions varied orthogonally to their validity. The belief bias effect, as well as the effect of validity, and the interaction between beliefs and validity, were not affected by reasoners' expectations regarding the number of problems they had to solve. The effect of beliefs and the belief by validity interaction were only marginally affected by the number of problems solved, despite adequate power to observe an effect. Thus, neither expectancy nor fatigue appear to have affected performance, suggesting that there are few drawbacks to using a within-subjects design. In contrast, however, a power analysis clearly established the desirability of using within-relative to between-subjects designs. Withinsubjects designs require far fewer participants to detect effects of comparable size; this was especially true for higher-order (interaction) effects. Finally, we provide a power analysis of within-and between-subjects designs that should be of general utility to researchers planning studies using proportions as a dependent measure.Key words: belief bias, deductive reasoning, statistical power, expectancy effects, carryover effectsThe default method for investigating deductive reasoning is a within-subjects design in which participants are asked to solve a large number of problems in a single sitting

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Section: Beliefs and Validity In Deductive Reasoningmentioning

confidence: 71%

Section: The Relative Merits Of Within-and Between-subjects Designsmentioning

confidence: 99%

A Power Struggle: Between- Vs. Within-Subjects Designs in Deductive Reasoning Research

Thompson

Campbell

2004

PSYCHOLOGIA -An International Journal of Psychological Sciences

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“…Sixteen syllogistic problem frames were used (see Appendix D): Eight problem frames controlled for atmosphere (Begg & Denny, 1969), conversion (Dickstein, 1975(Dickstein, , 1981Revlin, Leirer, Yopp, & Yopp, 1980), and figural effects (Dickstein, 1978), and eight controlled for atmosphere and figure, but not conversion. Although the design of this experiment did not require control of these structural effects, this decision allowed use of exactly the same problem frames in Experiments 2 and 3, where conclusion believability was manipulated.…”

Section: Methodsmentioning

confidence: 99%

Assessing the belief bias effect with ROCs: It's a response bias effect.

Dubé¹,

Rotello²,

Heit³

2010

Psychological Review

111

215

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A belief bias effect in syllogistic reasoning (Evans, Barston, & Pollard, 1983) is observed when subjects accept more valid than invalid arguments and more believable than unbelievable conclusions and show greater overall accuracy in judging arguments with unbelievable conclusions. The effect is measured with a contrast of contrasts, comparing the acceptance rates for valid and invalid arguments with believable and unbelievable conclusions. We show that use of this measure entails the assumption of a threshold model, which predicts linear receiver operating characteristics (ROCs). In 3 experiments, subjects made "valid"/"invalid" responses to syllogisms, followed by confidence ratings that allowed the construction of empirical ROCs; ROCs were also constructed from a base-rate manipulation in one experiment. In all cases, the form of the empirical ROCs was curved and therefore inconsistent with the assumptions of Klauer, Musch, and Naumer's (2000) multinomial model of belief bias. We propose a more appropriate, signal detection-based model of belief bias. We then use that model to develop theoretically sound and empirically justified measures of decision accuracy and response bias; those measures demonstrate that the belief bias effect is simply a response bias effect. Thus, our data and analyses challenge existing theories of belief bias because those theories predict an accuracy effect that our data suggest is a Type I error. Our results also provide support for processing theories of deduction that assume responses are driven by a graded argument-strength variable, such as the probability heuristic model proposed by Chater and Oaksford (1999).

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“…Specifically, subjects will tend to rate an argument as valid if they think that the conclusion is empirically true, and vice versa, irrespective of the textbook validity of the argument. The reality of the belief-bias effect has been questioned (Revlin & Leirer, 1978;Revlin, Leirer, Yopp, & Yopp, 1980), mainly on the grounds that some of the effects observed may be attributable to conversion effects due to subjects' idiosyncratic encoding of premises. However, Evans, Barston, and Pollard (1983) have demonstrated a strong belief-bias effect in experiments designed to control for both conversion and atmosphere effects.…”

Section: Henry Markovits and Guilaine Nantelmentioning

confidence: 99%

The belief-bias effect in the production and evaluation of logical conclusions

1989

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In this study, we examined whether adult subjects' beliefs regarding the empirical truth of a conclusion affected their production as well as their evaluation of a logical conclusion in a reasoning task. In addition, the relation between the ability to resolve an abstract reasoning problem correctly and the effect of belief-bias was examined. The subjects were given one of four paper-andpencil reasoning tasks, two of them using an evaluation paradigm, and two of them using a production paradigm. Each paradigm comprised either neutral problems or belief problems. The neutral problems were constructed to be as similar as possible to the belief problems, in order to control for extraneous factors. All four tasks also included an abstract reasoning problem. The results indicate a significant belief-bias effect for both the evaluation and the production tasks. Qualitative analysis indicated that the belief-bias effect was more pervasive in the production condition. In addition, the belief-bias effect was found to exist independently of the subjects' abstract reasoning ability. The results are discussed with reference to a two-stage model, in which belief is used to resolve uncertainties in inferentially produced conclusions.

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The belief-bias effect in formal reasoning: The influence of knowledge on logic

Cited by 153 publications

References 25 publications

A Power Struggle: Between- Vs. Within-Subjects Designs in Deductive Reasoning Research

A Power Struggle: Between- Vs. Within-Subjects Designs in Deductive Reasoning Research

Assessing the belief bias effect with ROCs: It's a response bias effect.

The belief-bias effect in the production and evaluation of logical conclusions

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