DOCSLIB.ORG

Design and Analysis of Simulated Choice Or Allocation Experiments in Travel Choice Modeling

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Design and Analysis of Simulated Choice Or Allocation Experiments in Travel Choice Modeling Transportation Research Record 890 11 forward as would testing the transferability of the cal Review, Vol. 78, 1971, pp. 71-80. coefficients of Stevens' Law among localities in 5. R.H. Erikson. The Effects of Perceived Place different geographic areas and with different char­ Attributes on the Cognition of Distance. Depart­ acteristics. Preliminary psychological research !il ment of Geography, Univ. of Iowa, Iowa City, suggests that it may be possible to develop a single Discussion Paper 23, 1975. equation that captures the relations between reality 6. R. Briggs. Urban Cognitive Distance. In Image and perception for all types of travel characteris­ and Environment: Cognitive Mapping andSpatial tics. Behavior (R.M. Downs and D. Shea, eds.), Aldine Another potentially fruitful area for further Publishing Co., Chicago, 1973. research would be an integration of the Stevens' Law 7. o. Bratfish. A Further Study of the Relation concept with the concept of cognitive dissonance. Between Subjective Distance and Emotional In­ The usefulness for transportation choice modeling of volvement. Acta Psychologica, Vol. 29, 1969, the theory of cognitive dissonance, with its impli­ pp. 244-255. cations regarding the interrelation of attitudes and 8. D. Cantor and S.K. Tagg. Distance Estimation in behavior, has been explored by Golob, Horowitz, and Cities. Environment and Behavior, Vol. 7, 1975, Wachs (14), Dumas and Dobson (15), and others. pp. 59-80. Further -application of the insights into human 9. R.A. Lowrey. Distance Concepts of Urban Resi­ behavior that are available in the literature on dents. Environment and Behavior, Vol. 2, 1970, psychology and marketing should prove beneficial in pp. 52-73. improving both knowledge of travel behavior and the 10. P. Burnett. Time Cognition and Urban Travel ability to forecast future behavior. Behavior. Presented at Geographical Perspec­ tives on the American City Conference, Phila­ ACKNOWLEDGMENT delphia, 1976. 11. E.J. Williams. Regression Analysis. Wiley, New The collection of the data on reported travel times York, 1959, pp. 129-137. and costs was supported by a grant to Northwestern 12. T.A. Domencich and D. McFadden. Urban Travel University from the U.S. Department of Transporta­ Demand. North-Holland, Amsterdam, Netherlands, tion. I would like to thank E. Hauer of the Univer­ 1975. sity of Toronto and several anonymous referees for 13. T.J. Adler and M. Ben-Akiva. Joint-Choice Model helpful comments. for Frequency, Destination, and Travel Mode for Shopping Trips. TRB, Transportation Research REFERENCES Record 569, 1976, pp. 136-150. 14. T.H. Golob, A.D. Horowitz, and M. Wachs. Atti­ 1. P.L. Watson. Problems Associated with Time and tude-Behaviour Relationships in Travel-Demand Cost Data Used in Travel Choice Modeling and Modelling. In Behavioural Travel Modelling Valuation of Time. HRB, Highway Research Record (D.A. Hensher~and P.R. Stopher, eds.), Croom 369, 1971, pp. 148-158. Helm, London, 1979. 2. A.H. Meyburg and Brog. Validity Problems in w. 15. J. Dumas and R. Dobson. Traveler Attitude: Empirical Analyses of Non-Home-Activity Pat­ Behavior Implications for the Operation and terns. TRB, Transportation Research Record 807, Promotion of Transport Systems. TRB, Transpor­ 1981, pp. 46-50. tation Research Record 723, 1979, pp. 64-71. 3. S.S. Stevens. On the Psychophysical Law. Psy­ chological Review, Vol. 64, 1957, pp. 153-181. 4. R. Teghtsoonian. On the Exponents in Stevens' Publication of this paper sponsored by Committee on Traveler Behavior and Law and the Constant in Ekman's Law. Psychologi- Values. Design and Analysis of Simulated Choice or Allocation Experiments in Travel Choice Modeling JORDAN J. LOUVIERE AND DAVID A. HENSHER A new approach for modeling traveler trade-offs and choices is proposed, de­ gained a following in the analysis and forecasting scribed, and illustrated. Based on research in psychology, marketing, and eco­ of travel behavior. If real choice data satisfy the nomics, a method for developing discrete choice models from controlled labo· conditions assumed in the statistical choice models, ratory simulation experiments is developed and presented. The method bor· it is possible to derive aggregate-level trade-offs rows statistical theory from discrete choice theory in econometrics and from and to simultaneously forecast choice behavior. the design of statistical experiments to marry work in trade-off analysis with Hence, methods based on revealed choice have high choice analysis. The method is illustrated by means of several travel-choice­ related examples that involve choice of mode and destination. Recent evidence external validity and practical applicability to of validity in forecasting the actual behavior of real markets is reviewed in sup­ strategic policy problems. port of the approach. Other approaches have recently gained attention-­ notably, laboratory simulation methods such as vari­ ations of conjoint measurement or trade-off analysis Since the early 1970s, the study of revealed-choice (7-9) and functional measurement (10-15), which are behavior based on the random utility derivations of the-primary methods of approach for-developing quan­ discrete choice theory in econometrics <.!-~) has titative descriptions of multiattribute individual 12 Transportation Research Record 890 and group judgments, trade-offs, or utilities. of choice models that at best can be tested only These approaches are based on the responses of weakly with revealed-choice data. travelers to hypothetical travel alternatives and not on their observed behavior. The former type of THEORY data is here called "intended choice" and the latter type "revealed choice". It is assumed that the derivations of discrete The intended-choice approaches to trade-off choice theory based on random utility notions are analysis have limitations that hamper their applica­ approximately true--that is, that the random utility bility, including the following: version of the Luce (20,21) choice axiom as derived by McFadden (5) and Yellot (22) holds for aggregate 1. One is usually forced to make untestable choices or allOcations: ~ assumptions about the functional form of the trade­ offs in practical applications. (I) 2. One must make assumptions about the relation between choice and utility that are untestable and are contrary to most assumptions in practical random where utility choice models. 3. It is difficult to incorporate individual p(alA, VjeA) probability of selecting alterna­ constraints on choice effectively except in an ad tive a from choice set A, of which hoc or post hoc fashion. a is a member, defined over all j 4. External validity assessment is less obvious members of A, including ai than with revealed-choice methods. utilities or scale values of a and j, respectivelyi and The revealed-choice methods, on the other hand, e = base of the natural logarithms. have major limitations: One normally assumes that the scale values (utili­ 1. One must make assumptions about functional ties) may be expressed as a linear in the parameters form a priori and, in contrast to the intended­ and additive functioni e.g., for alternative a, behavior methods, one cannot ever guarantee that it will be possible to test these assumptions ade­ (2) quately with real data. 2. One must make assumptions about mean utility where parameters or at least segmented mean parameters that are known from evidence to be often false Ua scale value of the ath alternative, (10,12,13,15,16) and that are used for the sake of b's constants to be estimated from the data, and tractability "rither than empirical reality. x's attributes of the ath alternative. 3. Measurement errors and correlations among variables cannot be controlled to any satisfactory Equation 1 states that the probability of choos­ degree, or at least have not historically been well ing any particular alternative from a set containing controlled (18). at least one other is expressible strictly as a 4. The forecasting accuracy of the models has function of conditional probabilities. Equation 2 been disappointing, which suggests that external imposes a linear in the parameters and additive validity of observations of choice is insufficient structure on the conditional probabilities to de­ to guarantee internal validity or forecast accuracy. scribe each alternative. In general, the attributes are specific to a particular alternative (e.g., al­ Recently, the consequences of failure to satisfy ternative a), but it is possible in some contexts to a number of these assumptions have been examined by treat the attributes as generic--i.e., attributes Horowitz (18,19). Suffice it to say that the that are common to all or some subset of alterna­ intended-choice approach can guarantee satisfaction tives. Other problems require mixtures of generic of many of the assumptions by design while sacrific­ and alternative specific attributes. ing immediate external estimation validity, whereas If one assumes Equation 1 to be true, it is pos­ the revealed-choice approach cannot guarantee satis­ sible to develop straightforward methods for col­ faction of its assumptions with real choice data but lecting data and estimating the parameters of the does have immediate external estimation validity. choice models derived therefrom. The results of This paper attempts to partially bridge the gap such choice studies are similar to those of conjoint between the two approaches by developing a method analysis, trade-off analysis, functional measure­ for estimating intended-choice models that satisfies
Load more

Recommended publications
  • Combining Choice Experiment and Attribute Best–Worst Scaling
    foods Article The Role of Trust in Explaining Food Choice: Combining Choice Experiment and Attribute y Best–Worst Scaling Ching-Hua Yeh 1,*, Monika Hartmann 1 and Nina Langen 2 1 Department of Agricultural and Food Market Research, Institute for Food and Resource Economics, University of Bonn, 53115 Bonn, Germany; [email protected] 2 Department of Education for Sustainable Nutrition and Food Science, Institute of Vocational Education and Work Studies, Technical University of Berlin, 10587 Berlin, Germany; [email protected] * Correspondence: [email protected]; Tel.: +49-(0)228-73-3582 The paper was presented in the conference of ICAE 2018. y Received: 31 October 2019; Accepted: 19 December 2019; Published: 3 January 2020 Abstract: This paper presents empirical findings from a combination of two elicitation techniques—discrete choice experiment (DCE) and best–worst scaling (BWS)—to provide information about the role of consumers’ trust in food choice decisions in the case of credence attributes. The analysis was based on a sample of 459 Taiwanese consumers and focuses on red sweet peppers. DCE data were examined using latent class analysis to investigate the importance and the utility different consumer segments attach to the production method, country of origin, and chemical residue testing. The relevance of attitudinal and trust-based items was identified by BWS using a hierarchical Bayesian mixed logit model and was aggregated to five latent components by means of principal component analysis. Applying a multinomial logit model, participants’ latent class membership (obtained from DCE data) was regressed on the identified attitudinal and trust components, as well as demographic information.
    [Show full text]
  • Integrated Choice and Latent Variable Models: a Literature Review on Mode Choice Hélène Bouscasse
    Integrated choice and latent variable models: A literature review on mode choice Hélène Bouscasse To cite this version: Hélène Bouscasse. Integrated choice and latent variable models: A literature review on mode choice. 2018. hal-01795630 HAL Id: hal-01795630 https://hal.archives-ouvertes.fr/hal-01795630 Preprint submitted on 18 May 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. GAEL Grenoble Applied Economic Laboratory Consumption – Energy - Innovation 8 201 / Integrated choice and latent variable 7 models: a literature review on mode 0 choice Hélène Bouscasse May 2018 JEL: C25, D9, R41 Working paper GAEL n° https://gael.univ-grenoble-alpes.fr/accueil-gael contact : [email protected] Integrated Choice and Latent Variable Models: a Literature Review on Mode Choice H´el`eneBouscasse a aUniv. Grenoble Alpes, CNRS, INRA, Grenoble INP, GAEL, 38000 Grenoble, France. [email protected] ABSTRACT Mode choice depends on observable characteristics of the transport modes and of the decision maker, but also on unobservable characteristics, known as latent variables. By means of an integrated choice and latent variable (ICLV) model, which is a com- bination of structural equation model and discrete choice model, it is theoretically possible to integrate both types of variables in a psychologically and economically sound mode choice model.
    [Show full text]
  • Cloud Computing Adoption Decision Modelling for Smes: from the PAPRIKA Perspective Salim Alismaili University of Wollongong
    University of Wollongong Research Online Faculty of Engineering and Information Sciences - Faculty of Engineering and Information Sciences Papers: Part A 2016 Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective Salim Alismaili University of Wollongong Mengxiang Li University of Wollongong, [email protected] Jun Shen University of Wollongong, [email protected] Publication Details Alismaili, S., Li, M. & Shen, J. (2016). Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective. Lecture Notes in Electrical Engineering, 375 597-615. Research Online is the open access institutional repository for the University of Wollongong. For further information contact the UOW Library: [email protected] Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective Abstract Springer Science+Business Media Singapore 2016.The popularity of cloud computing has been growing among enterprises since its inception. It is an emerging technology which promises competitive advantages, significant cost savings, enhanced business processes and services, and various other benefits. The aim of this paper is to propose a decision modelling using Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) for the factors that have impact in SMEs cloud computing adoption process. Disciplines Engineering | Science and Technology Studies Publication Details Alismaili, S., Li, M. & Shen, J. (2016). Cloud computing adoption decision modelling for SMEs: From the PAPRIKA perspective. Lecture Notes in Electrical Engineering, 375 597-615. This journal article is available at Research Online: http://ro.uow.edu.au/eispapers/6510 Cloud Computing Adoption Decision Modelling for SMEs: From the PAPRIKA Perspective Salim Alismaili 1, Mengxiang Li 2, Jun Shen 2 School of Computing and Information Technology, University of Wollongong, Australia 1 [email protected]; 2{mli, jshen}@uow.edu.au Abstract.
    [Show full text]
  • A Systematic Review of the Reliability and Validity of Discrete Choice
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Bangor University Research Portal A systematic review of the reliability and validity of discrete choice ANGOR UNIVERSITY experiments in valuing non-market environmental goods Rakotonarivo, Onjamirindra; Schaafsma, Marije; Hockley, Neal Journal of Environmental Management DOI: 10.1016/j.jenvman.2016.08.032 PRIFYSGOL BANGOR / B Published: 01/12/2016 Peer reviewed version Cyswllt i'r cyhoeddiad / Link to publication Dyfyniad o'r fersiwn a gyhoeddwyd / Citation for published version (APA): Rakotonarivo, O., Schaafsma, M., & Hockley, N. (2016). A systematic review of the reliability and validity of discrete choice experiments in valuing non-market environmental goods. Journal of Environmental Management, 183(1), 98-109. https://doi.org/10.1016/j.jenvman.2016.08.032 Hawliau Cyffredinol / General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. • Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.
    [Show full text]
  • Best–Worst Scaling Vs. Discrete Choice Experiments: an Empirical Comparison Using Social Care Data Article (Accepted Version) (Refereed)
    Dimitris Potoglou, Peter Burge, Terry Flynn, Ann Netten, Juliette Malley, Julien Forder and John E. Brazier Best–worst scaling vs. discrete choice experiments: an empirical comparison using social care data Article (Accepted version) (Refereed) Original citation: Potoglou, Dimitris and Burge, Peter and Flynn, Terry and Netten, Ann and Malley, Juliette and Forder, Julien and Brazier, John E. (2011) Best–worst scaling vs. discrete choice experiments: an empirical comparison using social care data. Social science & medicine, 72 (10). pp. 1717-1727. ISSN 0277-9536 DOI: 10.1016/j.socscimed.2011.03.027 © 2011 Elsevier Ltd. This version available at: http://eprints.lse.ac.uk/42278/ Available in LSE Research Online: April 2012 LSE has developed LSE Research Online so that users may access research output of the School. Copyright © and Moral Rights for the papers on this site are retained by the individual authors and/or other copyright owners. Users may download and/or print one copy of any article(s) in LSE Research Online to facilitate their private study or for non-commercial research. You may not engage in further distribution of the material or use it for any profit-making activities or any commercial gain. You may freely distribute the URL (http://eprints.lse.ac.uk) of the LSE Research Online website. This document is the author’s final manuscript accepted version of the journal article, incorporating any revisions agreed during the peer review process. Some differences between this version and the published version may remain. You are advised to consult the publisher’s version if you wish to cite from it.
    [Show full text]
  • Experimental Measurement of Preferences in Health and Healthcare Using Best-Worst Scaling: an Overview Axel C
    Mühlbacher et al. Health Economics Review (2016) 6:2 DOI 10.1186/s13561-015-0079-x RESEARCH Open Access Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview Axel C. Mühlbacher1*, Anika Kaczynski1, Peter Zweifel2 and F. Reed Johnson3 Abstract Best-worst scaling (BWS), also known as maximum-difference scaling, is a multiattribute approach to measuring preferences. BWS aims at the analysis of preferences regarding a set of attributes, their levels or alternatives. It is a stated-preference method based on the assumption that respondents are capable of making judgments regarding the best and the worst (or the most and least important, respectively) out of three or more elements of a choice- set. As is true of discrete choice experiments (DCE) generally, BWS avoids the known weaknesses of rating and ranking scales while holding the promise of generating additional information by making respondents choose twice, namely the best as well as the worst criteria. A systematic literature review found 53 BWS applications in health and healthcare. This article expounds possibilities of application, the underlying theoretical concepts and the implementation of BWS in its three variants: ‘object case’, ‘profile case’, ‘multiprofile case’. This paper contains a survey of BWS methods and revolves around study design, experimental design, and data analysis. Moreover the article discusses the strengths and weaknesses of the three types of BWS distinguished and offered an outlook. A companion paper focuses on special issues of theory and statistical inference confronting BWS in preference measurement. Keywords: Best-worst scaling, BWS, Experimental measurement, Healthcare decision making, Patient preferences Background: preferences in healthcare decision those affected, resource-allocation decisions will fail to making achieve optimal outcomes.
    [Show full text]
  • The Generalized Multinomial Logit Model
    The Generalized Multinomial Logit Model By Denzil G. Fiebig University of New South Wales Michael P. Keane University of Technology Sydney Jordan Louviere University of Technology Sydney Nada Wasi University of Technology Sydney June 20, 2007 Revised September 30, 2008 Abstract: The so-called “mixed” or “heterogeneous” multinomial logit (MIXL) model has become popular in a number of fields, especially Marketing, Health Economics and Industrial Organization. In most applications of the model, the vector of consumer utility weights on product attributes is assumed to have a multivariate normal (MVN) distribution in the population. Thus, some consumers care more about some attributes than others, and the IIA property of multinomial logit (MNL) is avoided (i.e., segments of consumers will tend to switch among the subset of brands that possess their most valued attributes). The MIXL model is also appealing because it is relatively easy to estimate. But recently Louviere et al (1999, 2008) have argued that the MVN is a poor choice for modelling taste heterogeneity. They argue that much of the heterogeneity in attribute weights is accounted for by a pure scale effect (i.e., across consumers, all attribute weights are scaled up or down in tandem). This implies that choice behaviour is simply more random for some consumers than others (i.e., holding attribute coefficients fixed, the scale of their error term is greater). This leads to what we call a “scale heterogeneity” MNL model (or S-MNL). Here, we develop a “generalized” multinomial logit model (G-MNL) that nests S-MNL and MIXL. By estimating the S-MNL, MIXL and G-MNL models on ten datasets, we provide evidence on their relative performance.
    [Show full text]
  • An R Package for Case 1 Best-Worst Scaling Mark H. White II
    Running head: BWSTOOLS 1 bwsTools: An R Package for Case 1 Best-Worst Scaling Mark H. White II National Coalition of Independent Scholars Author’s note: I would like to thank Anthony Marley, Geoff Hollis, Kenneth Massey, Guy Hawkins, and Geoff Soutar for their correspondence as well as the anonymous reviewers for their helpful comments. All code needed to reproduce analyses in this paper, as well as the source code for the package, can be found at https://osf.io/wb4c3/. Correspondence concerning this article should be addressed to Mark White, [email protected]. BWSTOOLS 2 Abstract Case 1 best-worst scaling, also known as best-worst scaling or MaxDiff, is a popular method for examining the relative ratings and ranks of a series of items in various disciplines in academia and industry. The method involves a survey respondent indicating the “best” and “worst” from a sample of items across a series of trials. Many methods exist for calculating scores at the individual and aggregate levels. I introduce the bwsTools package, a free and open-source set of tools for the R statistical programming language, to aid researchers and practitioners in the construction and analysis of best-worst scaling designs. This package is designed to work seamlessly with tidy data, does not require design matrices, and employs various published individual- and aggregate-level scoring methods that have yet to be employed in free software. Keywords : Best-worst scaling, MaxDiff, choice modeling, R BWSTOOLS 3 1. Introduction Important social and psychological processes require people to choose between alternatives. A high school, for example, might need new chemistry equipment and updated books—but the budget only supports one or the other.
    [Show full text]
  • Discrete Choice Experiments Are Not Conjoint Analysis
    A Service of Leibniz-Informationszentrum econstor Wirtschaft Leibniz Information Centre Make Your Publications Visible. zbw for Economics Louviere, Jordan J.; Flynn, Terry N.; Carson, Richard T. Article Discrete choice experiments are not conjoint analysis Journal of Choice Modelling Provided in Cooperation with: Journal of Choice Modelling Suggested Citation: Louviere, Jordan J.; Flynn, Terry N.; Carson, Richard T. (2010) : Discrete choice experiments are not conjoint analysis, Journal of Choice Modelling, ISSN 1755-5345, University of Leeds, Institute for Transport Studies, Leeds, Vol. 3, Iss. 3, pp. 57-72 This Version is available at: http://hdl.handle.net/10419/66796 Standard-Nutzungsbedingungen: Terms of use: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Documents in EconStor may be saved and copied for your Zwecken und zum Privatgebrauch gespeichert und kopiert werden. personal and scholarly purposes. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle You are not to copy documents for public or commercial Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich purposes, to exhibit the documents publicly, to make them machen, vertreiben oder anderweitig nutzen. publicly available on the internet, or to distribute or otherwise use the documents in public. Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, If the documents have been made available under an Open gelten abweichend von diesen Nutzungsbedingungen die
    [Show full text]
  • Is Best-Worst Scaling Suitable for Health State Valuation? a Comparison with Discrete Choice Experiments
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Aberdeen University Research Archive Is best-worst scaling suitable for health state valuation? A comparison with discrete choice experiments KRUCIEN Nicolas Health Economics Research Unit, University of Aberdeen, Institute of Applied Health Sciences, Foresterhill, Aberdeen, AB25 2QN. United Kingdom, Email: [email protected] WATSON Verity Health Economics Research Unit, University of Aberdeen, Institute of Applied Health Sciences, Foresterhill, Aberdeen, AB25 2QN. United Kingdom, Email: [email protected] RYAN Mandy Health Economics Research Unit, University of Aberdeen, Institute of Applied Health Sciences, Foresterhill, Aberdeen, AB25 2QN. United Kingdom, Email: [email protected] Corresponding Author Nicolas KRUCIEN Health Economics Research Unit University of Aberdeen Institute of Applied Health Sciences Aberdeen, AB25 2QN, UK Tel: 01224-437892 Fax 01224-437195 Email: [email protected] Abstract Health utility indices (HUIs) are widely used in economic evaluation. The best-worst scaling (BWS) method is being used to value dimensions of HUIs. However, little is known about the properties of this method. This paper investigates the validity of the BWS method to develop HUI, comparing it to another ordinal valuation method, the discrete choice experiment (DCE). Using a parametric approach we find a low level of concordance between the two methods, with evidence of preference reversals. BWS responses are subject to decision biases, with significant effects on individuals’ preferences. Non parametric tests indicate BWS data has lower stability, monotonicity and continuity compared to DCE data, suggesting the BWS provides lower quality data.
    [Show full text]
  • Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force F
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector VALUE IN HEALTH 16 (2013) 3–13 Available online at www.sciencedirect.com journal homepage: www.elsevier.com/locate/jval ISPOR TASK FORCE REPORT Constructing Experimental Designs for Discrete-Choice Experiments: Report of the ISPOR Conjoint Analysis Experimental Design Good Research Practices Task Force F. Reed Johnson, PhD1,*, Emily Lancsar, PhD2, Deborah Marshall, PhD3, Vikram Kilambi, BA/BS1, Axel Mu¨ hlbacher, PhD4,5, Dean A. Regier, PhD6, Brian W. Bresnahan, PhD7, Barbara Kanninen, PhD8, John F.P. Bridges, PhD9 1Health Preference Assessment Group, RTI Health Solutions, Research Triangle Park, NC, USA; 2Centre for Health Economics, Faculty of Business and Economics, Monash University, Melbourne, Victoria, Australia; 3Faculty of Medicine, Department of Community Health Sciences, University of Calgary, Calgary, Alberta, Canada; 4Duke University, Durham NC, USA; 5Hochschule Neubrandenburg, Neubrandenburg, Germany; 6Canadian Centre for Applied Research in Cancer Control, British Columbia Cancer Agency, Vancouver, Canada; 7Department of Radiology, University of Washington, Seattle, WA, USA; 8BK Econometrics, LLC, Arlington, VA, USA; 9Department of Health Policy and Management, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA ABSTRACT Stated-preference methods are a class of evaluation techniques for on the basis of study objectives and the statistical model researchers studying the preferences of patients and other stakeholders. While have selected for the study. The report outlines the theoretical require- these methods span a variety of techniques, conjoint-analysis ments for designs that identify choice-model preference parameters methods—and particularly discrete-choice experiments (DCEs)—have and summarizes and compares a number of available approaches for become the most frequently applied approach in health care in recent constructing experimental designs.
    [Show full text]
  • Estimation of Multinomial Logit Models in R : the Mlogit Packages
    Estimation of multinomial logit models in R : The mlogit Packages Yves Croissant Universit´ede la R´eunion Abstract mlogit is a package for R which enables the estimation of the multinomial logit models with individual and/or alternative specific variables. The main extensions of the basic multinomial model (heteroscedastic, nested and random parameter models) are implemented. Keywords:~discrete choice models, maximum likelihood estimation, R, econometrics. An introductory example The logit model is useful when one tries to explain discrete choices, i.e. choices of one among several mutually exclusive alternatives1. There are many useful applications of discrete choice modelling in different fields of applied econometrics, using individual data, which may be : • revealed preferences data which means that the data are observed choices of indi- viduals for, say, a transport mode (car, plane and train for example), • stated preferences data ; in this case, individuals face a virtual situation of choice, for example the choice between three train tickets with different characteristics : { A : a train ticket which costs 10 euros, for a trip of 30 minutes and one change, { B : a train ticket which costs 20 euros, for a trip of 20 minutes and no change, { C : a train ticket which costs 22 euros, for a trip of 22 minutes and one change. Suppose that, in a transport mode situation, we can define an index of satisfaction Vj for each alternative which depends linearly on cost (x) and time (z): 8 V = α + βx + γz <> 1 1 1 1 V2 = α2 + βx2 + γz2 > : V3 = α3 + βx3 + γz3 1For an extensive presentation of the logit model, see Train(2003) and Louiviere, Hensher, and Swait (2000).
    [Show full text]