On the Importance of Random Error in the Study of Probability Judgment. Part II: Applying the Stochastic Judgment Model to Detect Systematic Trends

✍ Scribed by DAVID V. BUDESCU; THOMAS S. WALLSTEN; WING TUNG AU

• Publisher: John Wiley and Sons
• Year: 1997
• Tongue: English
• Weight: 247 KB
• Volume: 10
• Category: Article
• ISSN: 0894-3257
• DOI: 10.1002/(sici)1099-0771(199709)10:3<173::aid-bdm261>3.0.co;2-6

✦ Synopsis

Erev, Wallsten, and Budescu (1994)

and Budescu, Erev, and Wallsten (1997) demonstrated that over-and undercon®dence often observed in judgment studies may be due, in part, to the presence of random error and its eects on the analysis of the judgments. To illustrate this fact they showed that a general model that assumes that overt responses representing (perfectly calibrated) true judgments perturbed by random error can replicate typical patterns observed in empirical studies. In this paper we provide a method for determining whether apparent overcon®dence in empirical data re¯ects a systematic bias in judgment or is an artifact due solely to the presence of error. The approach is based, in part, on the Wallsten and Gonza lez-Vallejo (1994) Stochastic Judgment Model (SJM). The new method is described in detail and is used to analyze results from a new study. The analysis indicates a clear overcon®dence eect, above and beyond the level predicted by a model assuming perfect calibration perturbed by random error.