John M. Rose

Constructing Efficient Stated Choice Experimental Designs

Abstract Stated choice (SC) experiments are often used in transportation studies for estimating and forecasting behaviour of travellers, road authorities, etc. This kind of experiment relies on underlying experimental designs. Whilst orthogonal designs are mainstream for practitioners, many researchers now realize that so‐called efficient designs are able to produce more efficient data in the sense that more reliable parameter estimates can be achieved with an equal or lower sample size. This paper describes several processes for generating SC experiments and is intended to give an overview of the current state‐of‐the‐art. Different methods are described.

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 (SC) studies. The paper examines how closely pseudo Monte Carlo, quasi Monte Carlo and Gaussian quadrature 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 analysed here (Halton, Sobol, and Modified Latin Hypercube Sampling) all clearly outperform the pseudo Monte Carlo draws. However, the Gaussian quadrature method examined in this paper, incremental Gaussian quadrature, outperforms all, and is therefore the recommended approximation method for the calculation of Bayesian efficiency of SC designs.

Factors influencing patient choice of dialysis versus conservative care to treat end-stage kidney disease

Background: For every patient with chronic kidney disease who undergoes renal-replacement therapy, there is one patient who undergoes conservative management of their disease. We aimed to determine the most important characteristics of dialysis and the trade-offs patients were willing to make in choosing dialysis instead of conservative care. Methods: We conducted a discrete choice experiment involving adults with stage 3–5 chronic kidney disease from eight renal clinics in Australia. We assessed the influence of treatment characteristics (life expectancy, number of visits to the hospital per week, ability to travel, time spent undergoing dialysis [i.e., time spent attached to a dialysis machine per treatment, measured in hours], time of day at which treatment occurred, availability of subsidized transport and flexibility of the treatment schedule) on patients’ preferences for dialysis versus conservative care. Results: Of 151 patients invited to participate, 105 completed our survey. Patients were more likely to choose dialysis than conservative care if dialysis involved an increased average life expectancy (odds ratio [OR] 1.84, 95% confidence interval [CI] 1.57–2.15), if they were able to dialyse during the day or evening rather than during the day only (OR 8.95, 95% CI 4.46–17.97), and if subsidized transport was available (OR 1.55, 95% CI 1.24–1.95). Patients were less likely to choose dialysis over conservative care if an increase in the number of visits to hospital was required (OR 0.70, 95% CI 0.56–0.88) and if there were more restrictions on their ability to travel (OR = 0.47, 95%CI 0.36–0.61). Patients were willing to forgo 7 months of life expectancy to reduce the number of required visits to hospital and 15 months of life expectancy to increase their ability to travel. Interpretation: Patients approaching end-stage kidney disease are willing to trade considerable life expectancy to reduce the burden and restrictions imposed by dialysis.

Factors that influence the decision to be an organ donor: a systematic review of the qualitative literature

BACKGROUND Transplantation is the treatment of choice for organ failure, but a worldwide shortage of suitable organs exists. We conducted a systematic review of qualitative studies that explored community attitudes towards living and deceased solid organ donation to inform strategies to improve organ donation rates. METHODS Medline, Embase, PsycINFO and EconLIT were searched. Qualitative studies that explored community attitudes towards living and deceased solid organ donation were included. A thematic synthesis of the results and conclusions reported by primary authors was performed. RESULTS Eighteen studies involving 1019 participants were identified. Eight themes emerged. The decision to be an organ donor was influenced by (i) relational ties; (ii) religious beliefs; (iii) cultural influences; (iv) family influences; (v) body integrity; (vi) previous interactions with the health care system-medical mistrust, validity of brain death and fear of early organ retrieval; (vii) the individuals knowledge about the organ donation process and (viii) major reservations about the process of donation, even in those who support organ donation. CONCLUSIONS This review of qualitative studies highlights that seemingly intractable factors, such as religion and culture, are often tied in with more complex issues such as a distrust of the medical system, misunderstandings about religious stances and ignorance about the donation process. Intervention that could be considered includes culturally appropriate strategies to engage minority groups, especially through religious or cultural leaders, and more comprehensively available information about the donation process and its positive outcomes.

Dialysis modality preference of patients with CKD and family caregivers: a discrete-choice study

BACKGROUND Dialysis modality preferences of patients with chronic kidney disease (CKD) and family caregivers are important, yet rarely quantified. STUDY DESIGN Prospective, unlabeled, discrete-choice experiment with random-parameter logit analysis. SETTING & PARTICIPANTS Adults with stages 3-5 CKD and caregivers educated about dialysis treatment options from 8 Australian renal clinics. PREDICTORS Preferences for and trade-offs between the dialysis treatment attributes of life expectancy, number of hospital visits per week, ability to travel, hours per treatment, treatment time of day, subsidized transport service, and flexibility of treatment schedule. OUTCOMES & MEASUREMENTS Results presented as ORs for preferring home-based or in-center dialysis to conservative care. RESULTS 105 predialysis patients and 73 family caregivers completed the study. Median patient age was 63 years, and mean estimated glomerular filtration rate was 18.1 (range, 6-34) mL/min/1.73 m(2). Median caregiver age was 61 years. Home-based dialysis (either peritoneal or home hemodialysis) was chosen by patients in 65% of choice sets; in-center dialysis, in 35%; and conservative care, in 10%. For caregivers, this was 72%, 25%, and 3%, respectively. Both patients and caregivers preferred longer rather than shorter hours of dialysis (ORs of 2.02 [95% CI, 1.51-2.70] and 2.67 [95% CI, 1.85-3.85] for patients and caregivers, respectively), but were less likely to choose nocturnal than daytime dialysis (ORs of 0.07 [95% CI, 0.01-0.75] and 0.03 [95% CI, 0.01-0.20]). Patients were willing to forgo 23 (95% CI, 19-27) months of life expectancy with home-based dialysis to decrease their travel restrictions. For caregivers, this was 17 (95% CI, 16-18) patient-months. LIMITATIONS Data were limited to stated preferences rather than actual choice of dialysis modality. CONCLUSIONS Our study suggests that it is rare for caregivers to prefer conservative nondialytic care for family members with CKD. Home-based dialysis modalities that enable patients and their family members to travel with minimal restriction would be strongly aligned with the preferences of both parties.

Using Classical Simulation-Based Estimators to Estimate Individual WTP Values

A number of papers have recently contrasted classical inference estimation methods for logit models with Bayesian methods. It has been argued that two particularly appealing features of the Bayesian approach are its relative simplicity in estimation, and its ability to derive, individual-specific willingness to pay (WTP) measures that are less problematic than the classical approaches in terms of extreme values and unexpected signs. This paper challenges this claim by deriving both population derived WTP measures and individual-specific values based on the classical mixed logit model, establishing the extent of unacceptable valuations. Our aim is not to estimate Bayesian contrasts per se but to show that the classical inference approach is likewise straightforward — indeed the individual-specific estimates are a by-product of the parameter estimation process. We also reveal the benefits of calculating WTP measures from ratios of individual parameters which are behaviourally more appealing approximations to the true values of each individual, in contrast to draws from population distributions that run the risk of allocating two parameters that are poorly juxtaposed in a relative sense, resulting in extreme value estimates. Our results suggest that while extreme values and unexpected signs cannot be ruled out (nor can they in the Bayesian framework), the overall superiority of the Bayesian method appears overstated. Both approaches have merit.

Community preferences for the allocation of solid organs for transplantation: a systematic review

Background. Organs for transplantation are a scarce community resource but community preferences and how they are incorporated into allocation policies are unclear. This systematic review aimed to ascertain community preferences for organ allocation and the principles underpinning these preferences. Methods. Medline, Embase, PsycINFO, EconLit, and gray literature databases were searched. Quantitative data were extracted, and a qualitative textual synthesis of the results and conclusions reported in each included study was performed. Results. Fifteen studies involving more than 5563 respondents were included. Seven themes describing community preferences for organ allocation were identified: (1) maximum benefit, to achieve maximum health gain in recipient survival and quality of life; (2) social valuation, to base preferences on societal gain; (3) moral deservingness, to consider the “worthiness” of recipients based on their social standing and lifestyle decisions; (4) prejudice, to make a judgement based on personal ideologic viewpoints; (5) “fair innings,” to provide an organ preferentially to the younger recipient giving opportunity for a “normal” life span and to those waiting for a first organ rather than a retransplant; (6) “first come, first served,” to allocate the organ to recipients wait-listed the longest; and (7) medical urgency, to allocate based on illness severity and saving life. Conclusions. Community preferences for organ allocation hinge on a complex balance of efficiency, social valuation, morality, fairness, and equity principles. Being a community-held resource, effective ways to identify and incorporate community preferences into allocation algorithms for solid organ transplantation are warranted.

Identifying commuter preferences for existing modes and a proposed Metro in Sydney, Australia with special reference to crowding

In 2009, the New South Wales government announced that it would be proceeding with a feasibility study to identify the patronage potential of a new Metro rail system for Sydney. As part of this study, a new modal choice study was undertaken to establish the role of traditional attributes such as travel times and costs (and more recently, reliability) but also somewhat neglected influences such as crowding, where the later has a critical role in the calculation of capacity needs at railway stations. This paper focuses on the commuter segment and develops a new stated choice experiment in which travellers are able to compare the proposed new Metro with existing available modal alternatives for access, linehaul and egress trip stages, with a particular emphasis on the incorporation of crowding represented by the availability of a seat vs. standing in existing and new public transport modes. We present the error component choice model together with estimates of mode-specific willingness to pay for travel time components, service frequency and crowding, that latter expressed in terms of the probability of getting a seat and the probability of avoiding standing.

Regret Minimization or Utility Maximization: It Depends on the Attribute

In this study we show how the coexistence of different decision rules can be accommodated in discrete choice models. Specifically, in this paper we present a generic hybrid model specification that allows for some attributes being processed using conventional linear-additive utility-maximization-based rules, while others are being processed using regret-minimization-based rules. We show that on two revealed and stated choice datasets particular specifications of hybrid models, containing both regret-based and utility-based attribute decision rules, outperform—in terms of model fit and out-of-sample predictive ability—choice models where all attributes are assumed to be processed by means of one and the same decision rule. However, in our data differences between models are very small. Implications, in terms of marginal willingness-to-pay measures (WtP), are derived for the different hybrid model specifications and applied in the context of the two datasets. It is found that in the context of our data hybrid WtP measures differ substantially from conventional utility-based WtP measures, and that the hybrid WtP specifications allow for a richer (choice-set-specific) interpretation of the trade-offs that people make.

A discrete choice experiment to obtain a tariff for valuing informal care situations measured with the CarerQol instrument

Background/Objective. Economic evaluations adopting a societal perspective need to include informal care whenever relevant. However, in practice, informal care is often neglected, because there are few validated instruments to measure and value informal care for inclusion in economic evaluations. The CarerQol, which is such an instrument, measures the impact of informal care on 7 important burden dimensions (CarerQol-7D) and values this in terms of general quality of life (CarerQol-VAS). The objective of the study was to calculate utility scores based on relative utility weights for the CarerQol-7D. These tariffs will facilitate inclusion of informal care in economic evaluations. Methods. The CarerQol-7D tariff was derived with a discrete choice experiment conducted as an Internet survey among the general adult population in the Netherlands (N = 992). The choice set contained 2 unlabeled alternatives described in terms of the 7 CarerQol-7D dimensions (level range: “no,”“some,” and “a lot”). An efficient experimental design with priors obtained from a pilot study (N = 104) was used. Data were analyzed with a panel mixed multinomial parameter model including main and interaction effects of the attributes. Results. The utility attached to informal care situations was significantly higher when this situation was more attractive in terms of fewer problems and more fulfillment or support. The interaction term between the CarerQol-7D dimensions physical health and mental health problems also significantly explained this utility. The tariff was constructed by adding up the relative utility weights per category of all CarerQol-7D dimensions and the interaction term. Conclusions. We obtained a tariff providing standard utility scores for caring situations described with the CarerQol-7D. This facilitates the inclusion of informal care in economic evaluations.