25. Multiple Imputation for Nonresponse in Surveys. By D. B. Rubin. ISBN 0 471 08705 X. Wiley, Chichester, 1987. 258 pp. £30.25.

Multiple Imputation for Nonresponse in Surveys

Reference TRANSP-OR-CONF-2006-048 URL: http://transp-or.epfl.ch/documents/proceedings/Bier03.pdf URL: http://www.strc.ch/Paper/bierlaire.pdf Record created on 2008-02-15, modified on 2017-12-15

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BIOGEME: a free package for the estimation of discrete choice models

Using Discrete Choice Experiments to Value Health and Health Care takes a fresh and contemporay look at the growing interest in the development and application of discrete choice experiments (DCEs) within the field of health economics. The authors have written it with the purpose of giving the reader a better understanding of issues raised in the design and application of DCEs in health economics. The use of this relatively new instrument to value health and health care has now evolved to the point where a general text is necessary. The few existing books in this area are either research monographs or focus almost entirely on more advanced topics. By contrast, this book serves as a general reference for those applying the technique to health care for the first time as well as more experienced practitioners. Thus the book is relevant to post-graduate students and applied researchers with an interest in the use of DCEs for valuing health and health care and has international appeal. The book comprises Chapters by highly regarded academics with experience of applying DCEs in the area of health. The first part of the book summarises how DCEs can be implemented, from experimental design to data analysis and the interpretation of results. In many ways this can be regarded as a crash course on the conduct of DCEs. Extensive reference is made throughout to other sources of literature where the interested reader can find further details. The book also includes a series of case studies illustrating the breadth of applications in health economics and some key methodological issues. Finally there is an overview of research issues discussed which the editors believe are at the leading edge of this field.

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Using discrete choice experiments to value health and health care

The state of the art of environmental valuation with discrete choice experiments

In this study, we investigate the extent to which experience affects individual preferences for specific electric vehicle characteristics, individual attitudes toward the environment, and the impact of the attitudes on the choice between an electric and a conventional vehicle. We use a two-wave stated preference experiment where data was collected before and after the respondents experienced an electric vehicle for three months. We estimate a hybrid choice model using jointly the stated choices before and after the test period. The results show that individual preferences change significantly after a real experience with an electric vehicle in the household. In particular, there are major changes in the preference for driving range, top speed, fuel cost, battery life and charging in city centres and train stations. In line with other studies, we find that environmental concern has a positive effect on the preference for EVs both before and after the test period, but the attitude itself and its effect on the choice of vehicle does not change.

On the stability of preferences and attitudes before and after experiencing an electric vehicle

We discuss the development of predictive choice models that go beyond the random utility model in its narrowest formulation. Such approaches incorporate several elements of cognitive process that have been identified as important to the choice process, including strong dependence on history and context, perception formation, and latent constraints. A flexible and practical hybrid choice model is presented that integrates many types of discrete choice modeling methods, draws on different types of data, and allows for flexible disturbances and explicit modeling of latent psychological explanatory variables, heterogeneity, and latent segmentation. Both progress and challenges related to the development of the hybrid choice model are presented.

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Axel Boersch-Supan

Papers

Hybrid choice models : Progress and challenges

Joint Estimation of Freight Transportation Decisions under Non-Random Sampling