Stated Choice Survey Design

By / August 14, 2019

Intensive Course

July 18 – July 19th, 2019
Berlin


A two day intensive course held at SurveyEngine and presented by Professor Michiel Bliemer on the design and construction of choice experiments.

Thanks to everyone who came, from Europe, from the US, from Pharma, Environment and Academia – it was a great success and a special thanks to Michiel for coming all the way from Sydney to present.

Below are a collection of online resources discussed or referenced or otherwise asked for during the workshop.

Experiment Design Resources

Choice Metrics website for Ngene software
http://www.choice-metrics.com

SAS raw orthogonal designs
http://support.sas.com/techsup/technote/ts723_Designs.txt

Neil Sloans library of orthogonal arrays
http://neilsloane.com/oadir

SurveyEngine Software

To get a free account, follow the link below to set up your own account. Be sure to use your email so we can identify you for special support.
https:://surveyengine.com/subscribe

A selection of starter survey files can be downloaded at the following link:
https://surveyengine.com/software/tutorials

For examples of some of the surveys presented in the workshop
https://surveyengine.com/software/live-software-demos/

Referenced Papers

Papers that came up in discussion on attribute order and learning effects (Thanks Juergen)

Norman R, Kemmler G, Viney R, Pickard S, Gamper E, Holzner B, Nerich V, King M. 2016.Order of presentation of dimensions did not systematically bias utility weights from a discrete choice experiment. Value in Health. 19(8):1033-1038. http://dx.doi.org/10.1016/j.jval.2016.07.003.

Hole AR, Norman R, Viney R. 2016. Response Patterns in Health State Valuation Using Endogenous Attribute Attendance and Latent Class Analysis. Health Economics 25(2):212-224. https://doi.org/10.1002/hec.3134.

Experimental Design Publications
  • Train, K.E. (2009), Discrete choice methods with simulation. Second edition, Cambridge University Press.
  • Hensher, D.A., J.M. Rose, and W.H. Greene (2015), Applied choice analysis. Second edition, Cambridge University Press.
  • Ben-Akiva, M., and S.R Lerman (1985), Discrete choice analysis: theory and applications to travel demand. MIT Press.
  • Louviere, J.J., D.A. Hensher, and J.D. Swait (2000), Stated choice methods: analysis and application. Cambridge University Press.
  • Rose, J.M., and M.C.J. Bliemer (2014) Stated choice experimental design theory: the who, the what and the why. In S. Hess and A. Daly (eds) Handbook of choice modelling. Edward-Elgar, UK, pp. 152-177.
  • Rose, J.M., and M.C.J. Bliemer (2011) Stated preference experimental design strategies. In: D.A. Hensher (ed.), Transport Economics: Critical concepts in economics (Vol. 1), Routledge, Oxford, UK, pp. 304-332.
  • Rose, J.M., Bain, S. and Bliemer, M.C.J. (2011) Experimental Design strategies for Stated Preference Studies; Dealing with Non-Market Goods, in Bennett, J. (ed.), International Handbook on Non-Marketed Environmental Valuation, Edward Elgar, Cheltenham, pp. 273-299.
  • Rose, J.M., and M.C.J. Bliemer (2009) Constructing efficient stated choice designs. Transport Reviews, Vol. 29, No. 5, pp. 587-617.
  • Bliemer, M.C.J., and J.M Rose (2009) Designing stated choice experiments: state-of-the-art. In R. Kitamura, T. Yoshii and T. Yamamoto (eds) The Expanding Sphere of Travel Behaviour Research. Emerald, UK, pp. 499-537.
  • Rose, J.M., and M.C.J. Bliemer (2008) Stated preference experimental design strategies. In D.A. Hensher and K.J. Button (eds) Handbook of Transport Modelling, Elsevier, 2nd edition, pp. 151-180.
  • Kuhfeld, W.F. (2006) Orthogonal arrays. Technical report TS723, SAS Institute.
  • Street, D.J., Burgess, L., & Louviere, J.J. (2005). Quick and easy choice sets: constructing optimal and nearly optimal stated choice experiments. International Journal of Research in Marketing, 22(4), 459–470.
  • Bliemer, M.C.J., J.M. Rose, and C.G. Chorus (2017) Detecting dominance in stated choice data and accounting for dominance-based scale differences in logit models. Transportation Research Part B, Vol. 102, pp. 83-104.
  • Huber, J., and K. Zwerina (1996) The importance of utility balance in efficient choice designs. Journal of Marketing Research, Vol. 33, pp. 307-317.
  • Kanninen, B.J. (2002) Optimal design for multinomial choice experiments. Journal of Marketing Research, Vol. 39, pp. 214-227.
  • Rose, J.M. and M.C.J. Bliemer (2013) Sample size requirements for stated choice experiments. Transportation, Vol. 40, No. 5, pp. 1021-1041.
  • De Bekker-Grob, E.W., B. Donkers, M.F. Jonker, and E.A. Stolk (2015) Sample size requirements for discrete choice experiments in healthcare: a practical guide. The Patient, Vol. 8(5), pp. 373-384.
  • Rose, J.M., and M.C.J. Bliemer (2012) Sample optimality in the design of stated choice experiments. In: Pendyala, R. and C. Bhat (eds) Travel behaviour research in the evolving world, IATBR, India, pp. 119-145.
  • Bliemer, M.C.J., and J.M. Rose (2011) Experimental design influences on stated choice outputs: an empirical study in air travel choice. Transportation Research Part A, Vol. 45, pp. 63-79.
  • Bliemer, M.C.J., and A.T. Collins (2016) On determining priors for the generation of efficient stated choice experimental designs. Journal of Choice Modelling, Vol. 21, pp. 10-14.
  • Sándor, Z., and M. Wedel (2001) Designing conjoint choice experiments using managers’ prior beliefs. Journal of Marketing Research, Vol. 38, pp. 430-444.
  • Bliemer, M.C.J., J.M. Rose, and S. Hess (2008) Approximation of Bayesian efficiency in experimental choice designs. Journal of Choice Modelling, Vol. 1, pp. 98-127.
  • Sándor, Z., and M. Wedel (2002) Profile construction in experimental choice designs for mixed logit models. Marketing Science, Vol. 21(4), pp. 455-475.
  • Bliemer, M.C.J., and J.M. Rose (2010) Construction of experimental designs for mixed logit models allowing for correlation across choice observations. Transportation Research Part B, Vol. 44, No. 6, pp. 720-734.
  • Rose, J.M., M.C.J. Bliemer, D.A. Hensher, and A. Collins (2008) Designing Efficient Stated Choice Experiments in the Presence of Reference Alternatives. Transportation Research Part B, Vol. 42, pp. 395-406.
  • Bliemer, M.C.J., and J.M. Rose (2010) Serial choice conjoint analysis for estimating discrete choice models. In S. Hess and A. Daly (eds) Choice modelling: the state-of-the-art and the state-of-the-practice. Emerald, Bingley, UK, pp. 139-161.
  • Bliemer, M.C.J., J.M. Rose, and D.A. Hensher (2009) Efficient stated choice experiments for estimating nested logit models. Transportation Research Part B, Vol. 43, No. 1, pp. 19-35.
  • Sándor, Z., and M. Wedel (2005) Heterogeneous conjoint choice designs. Journal of Marketing Research, Vol. 42, pp. 210-218.
  • Kessels, R., B. Jones, and P. Goos (2011) Bayesian optimal designs for discrete choice experiments with partial profiles. Journal of Choice Modelling, Vol. 4(3), pp. 52-74.
  • Bliemer, M.C.J., J.M. Rose, and M. Beck (2018) Generating partial choice set designs for stated choice experiments. Presented at the Annual Meeting of the International Association on Travel Behaviour Research, Santa Barbara CA, USA
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