Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Frits Traets, Daniel Gil Sanchez, Martina Vandebroek
Title: Generating Optimal Designs for Discrete Choice Experiments in R: The idefix Package
Abstract: Discrete choice experiments are widely used in a broad area of research fields to capture the preference structure of respondents. The design of such experiments will determine to a large extent the accuracy with which the preference parameters can be estimated. This paper presents a new R package, called idefix, which enables users to generate optimal designs for discrete choice experiments. Besides Bayesian D-efficient designs for the multinomial logit model, the package includes functions to generate Bayesian adaptive designs which can be used to gather data for the mixed logit model. In addition, the package provides the necessary tools to set up actual surveys and collect empirical data. After data collection, idefix can be used to transform the data into the necessary format in order to use existing estimation software in R.

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Paper: Generating Optimal Designs for Discrete Choice Experiments in R: The idefix Package     Download PDF (Downloads: 706)
Supplements:
idefix_1.0.1.tar.gz: R source package Download (Downloads: 70; 95KB)
v96i03.R: R replication code Download (Downloads: 70; 5KB)
v96i03-figures1+2.R: R replication code (Figures 1 & 2) Download (Downloads: 59; 3KB)

DOI: 10.18637/jss.v096.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.