期刊
JOURNAL OF STATISTICAL PLANNING AND INFERENCE
卷 141, 期 8, 页码 2519-2531出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jspi.2011.01.019
关键词
Bayesian optimal design; Rank-order experiment; Conjoint analysis; D-optimality; Rank-ordered conditional logit model
资金
- Fund for Scientific Research Flanders [G.0611.05]
- National Bank of Belgium [NB/06/05]
In a rank-order choice-based conjoint experiment, the respondent is asked to rank a number of alternatives of a number of choice sets. In this paper, we study the efficiency of those experiments and propose a D-optimality criterion for rank-order experiments to find designs yielding the most precise parameter estimators. For that purpose, an expression of the Fisher information matrix for the rank-ordered conditional logit model is derived which clearly shows how much additional information is provided by each extra ranking step. A simulation study shows that, besides the Bayesian D-optimal ranking design, the Bayesian D-optimal choice design is also an appropriate design for this type of experiments. Finally, it is shown that considerable improvements in estimation and prediction accuracy are obtained by including extra ranking steps in an experiment. (C) 2011 Elsevier B.V. All rights reserved.
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