As mentioned already, some of my papers are incorrectly cited, so here is a (handy?) list of the principal discrete choice related ones and the reasons for citing each 🙂
Flynn principal papers with primary relevance to choice models and reasons for citing
Coast J, Flynn TN, Sutton E, Al-Janabi H, Vosper J, Lavender S, Louviere JJ, Peters TJ. Investigating Choice Experiments for Preferences of Older People (ICEPOP): evaluative spaces in health economics. Journal of Health Services Research and Policy 2008;13(suppl 3):31-37
- Paper which introduces the wider context of the BWS work (quality of life and the ICEPOP programme)
Flynn TN, Louviere JJ, Peters TJ, Coast J. Best-Worst Scaling: What it can do for health care research and how to do it. Journal of Health Economics 2007;26(1):171-89.
- Original Case 2 (Profile case) user guide
- Uses old term – attribute case – since dropped
- But NOT the first case 2 published study in health – see Szeinbach et al 1999: Using conjoint analysis to evaluate health state preferences
- Contrasts maxdiff and marginal models (though unfortunately not called these in the paper)
Lancsar E, Louviere JJ, Flynn TN. Several methods to estimate relative attribute impact in stated preference experiments. Social Science and Medicine, 2007;64:1738-1753.
- First paper to discuss attribute IMPACT versus IMPORTANCE and how to get the former from BWS (amongst other techniques applied to DCE data)
Flynn TN, Louviere JJ, Peters TJ, Coast J. Estimating preferences for a dermatology consultation using Best-Worst Scaling: Comparison of various methods of analysis. BMC Medical Research Methodology 2008; 8:76.
- Corrected the coding for the marginal sequential model from JHE article in order that model summary statistics be correct
- Showed no difference in results from different models
- Illustration of heterogeneity using effects coding and thereby showing how splitting out attribute impact out can be useful
Marley AAJ, Flynn TN, Louviere JJ. Probabilistic Models of Set-Dependent and Attribute-Level Best-Worst Choice. Journal of Mathematical Psychology 2008; 52:281-296.
- Paper with mathematical proof of Case 2 estimator properties
- The proof that you can’t, in fact, get attribute importance from BWS (contrary to McIntosh & Louviere original claim) though you do go a long way toward it, getting attribute IMPACT, (discussed in more detail in JOCM 2013)
- Review of the literature on discrete choice tasks showing that despite 40 years of research estimation of attribute IMPORTANCE (in a discrete choice tasks framework) remains elusive
- Presented hypothetical example of how manipulating context across two DCEs would finally allow estimation of attribute importance – this principle is used by Flynn et al (JOCM 2013)
Flynn TN, Marley AAJ, Louviere JJ, Peters TJ, Coast J. Rescaling quality of life tariffs from discrete choice experiments for use as QALYs: a cautionary tale. Population Health Metrics 2008; 6:6
- Key paper showing why putting the death state into any RUT-based model is wrong.
- Also first paper to discuss why the choice of health states used in any RUT-based model must take into account how scale might vary as a result – e.g. two states far apart on the latent health scale will have a large variance scale factor, much larger than two states close together on the latent health scale
Louviere JJ, Flynn TN. Using Best-Worst Scaling Choice Experiments To Measure Public Perceptions and Preferences for Healthcare Reform in Australia. The Patient: Patient-Centered Outcomes Research 2010;3(4):275-283
- First Case 1 paper in health
Flynn TN, Peters TJ, Coast J. Quantifying response shift or adaptation effects in quality of life by synthesising best-worst scaling and discrete choice data. Journal of Choice Modelling 2013;6:34-43
- Hopefully seminal paper as the first empirical application of the proposed model put forward by Marley et al (2008) and discussed by Flynn (2010) in which context is varied in order to get attribute importance.
- This is used in an attempt to quantify response shift (adaptation) in a quality of life context.
Flynn TN, Louviere JJ, Peters TJ, Coast J. Using discrete choice experiments to investigate heterogeneity in preferences for quality of life. Variance scale heterogeneity matters. Social Science and Medicine 2010; 70:1957-1965
- First paper in health to demonstrate the scale adjusted latent class (SALC) model to attempt to properly adjust for scale (the G-MNL being the other model)
- Hypothesises how individual level valuations of health/QoL states is now possible
Louviere JJ, Flynn TN, Carson R. Discrete choice experiments are not conjoint analysis. The Journal of Choice Modelling 2010;3(3):57-72
- Paper discussed theoretical underpinnings of DCEs
- Why these are not part of the conjoint measurement paradigm in academia,
- Why we need to be aware that we are concentrating on a tiny part of the whole decision making process that humans use
Flynn TN. Valuing citizen and patient preferences in health: recent developments in three types of best-worst scaling. Expert Review of Pharmacoeconomics & Outcomes Research 2010; 10(3):259-267.
- First paper to set out the definitive naming of all three types (“Cases”) of BWS
- The object case – Case 1, where the choice options are non-attribute based simple options,
- The profile case – Case 2, where the choice options are attribute levels within a profile-based framework
- The multi-profile case – Case 3, where the choice options are multi-attribute profiles
- These names were chosen by the inventor of BWS (Jordan Louviere) and agreed by the three authors writing the definitive textbook (CUP 2014 forthcoming).
- First paper in health to use the best-minus-worst scores (the “scores”), from Marley & Louviere (2005) in summarising outcomes
Flynn TN. Using conjoint analysis and choice experiments to estimate quality adjusted life year values: issues to consider. Pharmacoeconomics 2010;28(9):711-722
- Paper notes likely problems getting interactions from Case 2
- First paper to propose various options in valuing health states in discrete choice framework, ranging from using TTO to rescale estimates from a DCE without a duration attribute (cheap but not ideal) to including duration as an attribute (expensive, but theoretically more appealing)
- First paper to discuss how Case 2 might change the context of the problem under investigation from a traditional DCE – and how the researcher should consider this when tempted to make inferences about the validity of one or both types of task (within- versus between-profile tasks)
- Further discussion of how variance scale is important to consider in discrete choice based valuation studies in health
- Further discussion of why including the “dead state” is wrong
- Warns health economists about the possibility that respondents might interact with the design (“demand artefacts”) and the need for common designs in order that there is no confounding of design with utilities
Hawkins GE, Marley AAJ, Heathcote A, Flynn TN, Louviere JJ, Brown SD. Integrating cognitive process and descriptive models of attitudes and preferences. Cognitive Science (in press, accepted 23 May 2013
- Collection of response times alongside DCE data
- How, for the first time, inferences from a stated preference RUT-based model have been proved from a proper process model (the LBA).
- Uses BWS as a vehicle for collecting data and providing additional proof of process model
Louviere JJ, Lings I, Islam T, Gudergan S, Flynn TN. An Introduction to the Application of (case 1) Best-Worst Scaling in Marketing Research. International Journal of Research in Marketing 2013;30(3):292-303.
- First user guide paper for Case 1 but in marketing.
- Many of the techniques already in use in early health papers including a recent paper in SSM by Swiss researchers.
Potoglou D, Burge P, Flynn TN, Netten A, Malley J, Forder J, Wall B, Brazier J. Best-worst Scaling vs. Discrete Choice Experiments: An Empirical Comparison using Social Care Data. Social Science and Medicine 2011;72(10):1717-1727
- First comparison of DCE and Case 2 data, though not in a fully scale-adjusted model.
Coast J, Al-Janabi H, Sutton E, Horrocks S, Vosper J, Swancutt D, Flynn TN. Using qualitative methods for attribute development for discrete choice experiments: issues and recommendations. Health Economics 2012;21(6):730-741
- Paper dealing with issues raised by Louviere, Hensher & Swait (2001 book) in terms of providing guidance on development of attributes
- Compares various qualitative methods in the light of experiences from the ICEPOP programme