DrukkerD. M., and GatesR.2006. Generating Halton sequences using Mata. Stata Journal6: 214–228.
2.
FiebigD. G., and HallJ.2004. Discrete choice experiments in the analysis of health policy. Productivity Commission Conference: Quantitative Tools for Microeconomic Policy Analysis6: 119–136.
3.
FiebigD. G., KeaneM. P., LouviereJ., and WasiN.2010. The generalized multinomial logit model: Accounting for scale and coefficient heterogeneity. Marketing Science29: 393–421.
4.
FiebigD. G., KnoxS., VineyR., HaasM., and StreetD. J.2011. Preferences for new and existing contraceptive products. Health Economics20(Suppl.): 35–52.
5.
GreeneW. H., and HensherD. A.2010. Does scale heterogeneity across individuals matter? An empirical assessment of alternative logit models. Transportation37: 413–428.
6.
HaltonJ. H.1964. Algorithm 247: Radical-inverse quasi-random point sequence. Communications of the ACM7: 701–702.
7.
HoleA. R.2007. Fitting mixed logit models by using maximum simulated likelihood. Stata Journal7: 388–401.
8.
KeaneM., and WasiN. Forthcoming. Comparing alternative models of heterogeneity in consumer choice behavior. Journal of Applied Econometrics.
9.
KnoxS. A., VineyR. C., GuY., HoleA. R., FiebigD. G., StreetD. J., HaasM. R., WeisbergE., and BatesonD.2013. The effect of adverse information and positive promotion on women's preferences for prescribed contraceptive products. Social Science and Medicine83: 70–80.
10.
LouviereJ., and EagleT.2006. Confound it! That pesky little scale constant messes up our convenient assumptions. InProceedings of the Sawtooth Software Conference, 211–228. Sequim, WA: Sawtooth Software.
11.
LouviereJ. J., MeyerR. J., BunchD. S., CarsonR. T., DellaertB., HanemannW. M., HensherD., and IrwinJ.1999. Combining sources of preference data for modeling complex decision processes. Marketing Letters10: 205–217.
12.
LouviereJ. J., StreetD., BurgessL., WasiN., IslamT., and MarleyA. A. J.2007. Modeling the choices of individual decision-makers by combining efficient choice experiment designs with extra preference information. Journal of Choice Modelling1: 128–163.
13.
LouviereJ. J., StreetD., CarsonR., AinslieA., DeshazoJ. R., CameronT., HensherD., KohnR., and MarleyT.2002. Dissecting the random component of utility. Marketing Letters13: 177–193.
14.
McFaddenD., and TrainK.2000. Mixed MNL models for discrete response. Journal of Applied Econometrics15: 447–470.
15.
ReveltD., and TrainK.2000. Customer-specific taste parameters and mixed logit: Households’ choice of electricity supplier. Working Paper No. E00-274, Department of Economics, University of California, Berkeley.
16.
TrainK. E.2009. Discrete Choice Methods with Simulation. 2nd ed. Cambridge: Cambridge University Press.
