Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments
نویسندگان
چکیده
منابع مشابه
Causal Inference in Conjoint Analysis: Understanding Multidimensional Choices via Stated Preference Experiments
Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and ...
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Survey experiments are a core tool for causal inference. Yet, the design of classical survey experiments prevents them from identifying which components of a multidimensional treatment are influential. Here, we show how conjoint analysis, an experimental design yet to be widely applied in political science, enables researchers to estimate the causal effects of multiple treatment components and ...
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Constructing stated-preference (sp) experiments from a choice that the respondent made in a revealed-preference setting can enhance the realism of the sp task and the efficacy of preference revelation. However, the practice creates dependence between the sp attributes and unobserved factors, contrary to the independence assumption that is maintained for standard estimation procedures. We descri...
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Transportation researchers have recently introduced a stated-preference (sp) method in which the attributes of the sp alternatives are based on the choice that the respondent made in a real-world setting. This practice can enhance the realism of the sp task and the efficacy of preference revelation. However, the practice creates dependence between the sp attributes and unobserved factors, contr...
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ژورنال
عنوان ژورنال: Political Analysis
سال: 2014
ISSN: 1047-1987,1476-4989
DOI: 10.1093/pan/mpt024