Constructing Efficient Choice Experiments

Research on the construction of efficient designs for stated choice (SC) experiments has been limited to either unlabeled experiments with generic parameter estimates or labeled experiments with alternative specific parameter estimates. Designs combining both generic and alternative specific parameters have not yet been addressed. In this paper, by deriving the asymptotic (co)variance matrix for the most general MNL model, the authors are able to demonstrate how efficient experiments that allow for the estimation of both types of estimates may be generated. The authors go onto show how estimation of the asymptotic (co)variance matrix may also be used to determine sample size requirements for SC experiments

Approximation of Bayesian Efficiency in Experimental Choice Designs

This paper compares different types of simulated draws over a range of number of draws in generating Bayesian efficient designs for stated choice studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and polynomial cubature methods are able to replicate the true levels of Bayesian efficiency for SC designs of various dimensions. The authors conclude that the predominantly employed method of using pseudo Monte Carlo draws is unlikely to result in leading to truly Bayesian efficient SC designs. The quasi Monte Carlo methods analyzed here (Halton, Sobol, and Modified Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the polynomial cubature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of stated choice designs

Bayesian D-Optimal Choice Designs for Mixtures

__Abstract__ \n \nConsumer products and services can often be described as mixtures of ingredients. Examples are the mixture of ingredients in a cocktail and the mixture of different components of waiting time (e.g., in-vehicle and out-of-vehicle travel time) in a transportation setting. Choice experiments may help to determine how the respondents\' choice of a product or service is affected by the combination of ingredients. In such studies, individuals are confronted with sets of hypothetical products or services and they are asked to choose the most preferred product or service from each set. \n \nHowever, there are no studies on the optimal design of choice experiments involving mixtures. We propose a method for generating an optimal design for such choice experiments. To this end, we first introduce mixture models in the choice context and next present an algorithm to construct optimal experimental designs, assuming the multinomial logit model is used to analyze the choice data. To overcome the problem that the optimal designs depend on the unknown parameter values, we adopt a Bayesian D-optimal design approach. We also consider locally D-optimal designs and compare the performance of the resulting designs to those produced by a utility-neutral (UN) approach in which designs are based on the assumption that individuals are indifferent between all choice alternatives. We demonstrate that our designs are quite different and in general perform better than the UN designs

Dealing with the health state ‘dead’ when using discrete choice experiments to obtain values for EQ-5D-5L heath states - Springer

__Abstract__ __Objective__ : To evaluate two different methods to obtain a dead (0)—full health (1) scale for EQ-5D-5L valuation studies when using discrete choice (DC) modeling. __Method__ : The study was carried out among 400 respondents from Barcelona who were representative of the Spanish population in terms of age, sex, and level of education. The DC design included 50 pairs of health states in five blocks. Participants were forced to choose between two EQ-5D-5L states (A and B). Two extra questions concerned whether A and B were considered worse than dead. Each participant performed ten choice exercises. In addition, values were collected using lead-time trade-off (lead-time TTO), for which 100 states in ten blocks were selected. Each participant performed five lead-time TTO exercises. These consisted of DC models offering the health state ‘dead’ as one of the choices—for which all participants’ responses were used (DCdead)—and a model that included only the responses of participants who chose at least one state as worse than dead (WTD) (DCWTD). The study also estimated DC models rescaled with lead-time TTO data and a lead-time TTO linear model. __Results__ : The DCdead and DCWTD models produced relatively similar results, although the coefficients in the DCdead model were slightly lower. The DC model rescaled with lead-time TTO data produced higher utility decrements. Lead-time TTO produced the highest utility decrements. __Conclusions__: The incorporation of the state ‘dead’ in the DC models produces results in concordance with DC models that do not include ‘dead’

Estimation of New Monetary Valuations of Travel Time, Quality of Travel, and Safety for Singapore

A large-scale study in Singapore estimated new monetary valuations for travel time, quality of travel, and safety covering different modes and journey components. A wide-ranging stated-choice survey was conducted on a large, representative sample. The empirical work pushed the boundaries of the international state of the practice in choice modeling by relying on mixed logit models with all model components being random and a full covariance matrix being estimated. Detailed results are presented, and the values are contrasted with those from the previous study, conducted in 2008

Protective behaviour of citizens to transport accidents involving hazardous materials: A discrete choice experiment applied to populated areas nearby waterways

Background To improve the information for and preparation of citizens at risk to hazardous material transport accidents, a first important step is to determine how different characteristics of hazardous material transport accidents will influence citizens' protective behaviour. However, quantitative studies investigating citizens' protective behaviour in case of hazardous material transport accidents are scarce. Methods A discrete choice experiment was conducted among subjects (19-64 years) living in the direct vicinity of a large waterway. Scenarios were described by three transport accident characteristics: odour perception, smoke/vapour perception, and the proportion of people in the environment that were leaving at their own discretion. Subjects were asked to consider each scenario as realistic and to choose the alternative that was most appealing to them: staying, seekin

Patients' and urologists' preferences for prostate cancer treatment: A discrete choice experiment

__Abstract__ Background: Patients' preferences are important for shared decision making. Therefore, we investigated patients' and urologists' preferences for treatment alternatives for early prostate cancer (PC). Methods: A discrete choice experiment was conducted among 150 patients who were waiting for their biopsy results, and 150 urologists. Regression analysis was used to determine patients' and urologists' stated preferences using scenarios based on PC treatment modality (radiotherapy, surgery, and active surveillance (AS)), and risks of urinary incontinence and erectile dysfunction.Results:The response rate was 110 out of 150 (73%) for patients and 50 out of 150 (33%) for urologists. Risk of urinary incontinence was an important determinant of both patients' and urologists' stated preferences for PC treatment (P<0.05). Treatment modality also influenced patients' stated preferences (P<0.05), whereas the risk of erectile dysfunction due to radiotherapy was mainly important to urologists (P<0.05). Both patients and urologists preferred AS to radical treatment, with the exception of patients with anxious/depressed feelings who preferred radical treatment to AS. Conclusion: Although patients and urologists generally may prefer similar treatments for PC, they showed different trade-offs between various specific treatment aspects. This implies that urologists need to be aware of potential differences compared with the patient's perspective on treatment decisions in shared decision making on PC treatment