On determining priors for the generation of efficient stated choice experimental designs
| Autor: | Michiel C.J. Bliemer, Andrew T. Collins |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
050210 logistics & transportation
Choice set business.industry Process (engineering) Design of experiments 05 social sciences Sample (statistics) Scale (descriptive set theory) Machine learning computer.software_genre Ranking Simple (abstract algebra) Modeling and Simulation 0502 economics and business Prior probability Econometrics Economics 050202 agricultural economics & policy Artificial intelligence Statistics Probability and Uncertainty business computer |
| Zdroj: | Journal of Choice Modelling. 21:10-14 |
| ISSN: | 1755-5345 |
| Popis: | Bayesian priors are required in order to generate efficient and robust experimental designs for stated choice surveys. Although such priors are commonly obtained through a pilot study, in this paper we provide a simple alternative in which the analyst depends only on their own expert judgement and possibly on parameter estimates obtained from the literature. The process consists of ranking attribute levels, balancing choice tasks to obtain trade-offs, and setting probabilities in sample choice tasks to establish scale. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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