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Title:Modeling preference noise and response noise in risky choice: Commentary on Bhatia and Loomes (2017)
Author(s):Fields, Bryanna
Advisor(s):Regenwetter, Michel
Contributor(s):Köhn, Hans-Friedrich
Department / Program:Psychology
Discipline:Psychology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:M.S.
Genre:Thesis
Subject(s):Decision making, modeling noise, nonparametric models
Abstract:Decision making research often heavily relies on deterministic modeling approaches. However, choice data are stochastic and therefore need to be modeled probabilistically. According to one probabilistic modeling approach, a decision maker has a fixed preference, but makes errors when selecting the utility-maximizing option. In another approach, a decision maker makes no errors, but his preference itself is probabilistic. Bhatia and Loomes (2017) refer to the first approach as "response noise" and the second approach as "preference noise." To avoid incorrect conclusions of a decision maker's underlying preferences, Bhatia and Loomes (2017) strongly advocate for modeling both types of noise simultaneously. In this commentary, we discuss the methods of Bhatia and Loomes (2017) and revisit a hybrid model, which models response and preference noise simultaneously, to address some limitations of these methods. Furthermore, we illustrate the hybrid model, discuss further refinements to the model, and illustrate model fit using data from hypothetical decision makers.
Issue Date:2019-04-23
Type:Text
URI:http://hdl.handle.net/2142/105075
Rights Information:Copyright 2019 Bryanna Fields
Date Available in IDEALS:2019-08-23
Date Deposited:2019-05


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