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Stated Choice Methods: Analysis and Applications
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In this article, stated preference models and methods are presented for choosing a residential telecommunications bundle and a choice model for a particular set of products and services, as a way of life for individuals.Abstract:
1. Choosing as a way of life Appendix A1. Choosing a residential telecommunications bundle 2. Introduction to stated preference models and methods 3. Choosing a choice model Appendix A3. Maximum likelihood estimation technique Appendix B3. Linear probability and generalised least squares models 4. Experimental design 5. Design of choice experiments Appendix A5. 6. Relaxing the IID assumption-introducing variants of the MNL model Appendix A6. Detailed characterisation of the nested logit model Appendix B6. Advanced discrete choice methods 7. Complex, non-IID multiple choice designs 8. Combining sources of preference data 9. Implementing SP choice behaviour projects 10. Marketing case studies 11. Transportation case studies 12. Environmental valuation case studies 13. Cross and external validity of SP models.read more
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Discrete Choice Methods with Simulation
TL;DR: In this paper, the authors describe the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation, and compare simulation-assisted estimation procedures, including maximum simulated likelihood, method of simulated moments, and methods of simulated scores.
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Conjoint analysis applications in health--a checklist: a report of the ISPOR Good Research Practices for Conjoint Analysis Task Force.
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Incentive and informational properties of preference questions
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Understanding heterogeneous preferences in random utility models: a latent class approach.
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