Does anchoring cause overconfidence only in experts?

Expanding the Space of Cognitive Science - Proceedings of the 33rd Annual Meeting of the Cognitive Science Society, CogSci 2011

Volumn , Issue , 2011, Pages 1947-1952

  Bruza, Belinda ^a   Welsh, Matthew B ^a   Navarro, Daniel J ^a   Begg, Stephen H ^a  

^a UNIVERSITY OF ADELAIDE   (Australia)

Author keywords

anchoring; number preference; overconfidence; precision

Indexed keywords

ADJUSTMENT HEURISTICS; ANCHORINGS; ELICITATION METHODS; EXPERT AND NOVICES; INITIAL ESTIMATE; NUMBER PREFERENCE; OVERCONFIDENCE; PRECISION; RANGE BLOCK;

EID: 84980018339     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (3)

1. Variables violated the assumptions of standard parametric procedures; therefore 20% trimmed means are reported to improve robustness against outliers and skewness (Keselman, Algina, Lix, Wilcox, & Deering, 2008). Confidence intervals around these means were calculated using a percentile bootstrap method with 10,000 bootstrap samples (see Erceg-Hurn & Mirosevich, 2008).
2. Because data was skewed, a rank transformation was performed on all observations for the range of estimates, with the lowest rank of “1” assigned to the smallest observation (see Conover & Iman, 1981).
3. Distributions of variables were skewed. Thus, a rank transformation was performed on all observations, with the lowest rank of “1” assigned to the smallest observation.