IDEAS home Printed from https://ideas.repec.org/a/eee/eejocm/v32y2019ic3.html
   My bibliography  Save this article

An R package and tutorial for case 2 best–worst scaling

Author

Listed:
  • Aizaki, Hideo
  • Fogarty, James

Abstract

Case 2 (profile case) best–worst scaling (BWS) is a question-based survey method for measuring preferences for attribute levels. Several existing R packages help to implement the construction of Case 2 BWS questions (profiles) and the discrete choice analysis of the responses to the questions. Structuring the dataset for Case 2 BWS analysis is, however, complicated: there are several model variants for the analysis, and independent variables are set according to the variants. This complexity makes it difficult for non-expert users to prepare datasets for Case 2 BWS analysis. To improve the capability of R with respect to Case 2 BWS and facilitate easier data analysis, the package support.BWS2 has been developed. The package provides a function to map raw survey data into a format suitable for analysis, and also includes other useful functions, such as a function to calculate count-based BWS scores. A free online tutorial for Case 2 BWS in R has also been made available. These works make it easier for those new to Case 2 BWS to complete research using R, and facilitate the use of Case 2 BWS in various research fields.

Suggested Citation

  • Aizaki, Hideo & Fogarty, James, 2019. "An R package and tutorial for case 2 best–worst scaling," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    • Handle: RePEc:eee:eejocm:v:32:y:2019:i:c:3
    DOI: 10.1016/j.jocm.2019.100171
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1755534519300569
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jocm.2019.100171?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    2. Flynn, Terry Nicholas & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2010. "Using discrete choice experiments to understand preferences for quality of life. Variance-scale heterogeneity matters," Social Science & Medicine, Elsevier, vol. 70(12), pages 1957-1965, June.
    3. Flynn, Terry N. & Louviere, Jordan J. & Peters, Tim J. & Coast, Joanna, 2007. "Best-worst scaling: What it can do for health care research and how to do it," Journal of Health Economics, Elsevier, vol. 26(1), pages 171-189, January.
    4. Marieke G. M. Weernink & Janine A. Til & Catharina G. M. Groothuis-Oudshoorn & Maarten J. IJzerman, 2017. "Patient and Public Preferences for Treatment Attributes in Parkinson’s Disease," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 10(6), pages 763-772, December.
    5. Kei Long Cheung & Ben F. M. Wijnen & Ilene L. Hollin & Ellen M. Janssen & John F. Bridges & Silvia M. A. A. Evers & Mickael Hiligsmann, 2016. "Using Best–Worst Scaling to Investigate Preferences in Health Care," PharmacoEconomics, Springer, vol. 34(12), pages 1195-1209, December.
    6. Potoglou, Dimitris & Burge, Peter & Flynn, Terry & Netten, Ann & Malley, Juliette & Forder, Julien & Brazier, John E., 2011. "Best-worst scaling vs. discrete choice experiments: An empirical comparison using social care data," Social Science & Medicine, Elsevier, vol. 72(10), pages 1717-1727, May.
    7. Jennifer A. Whitty & Julie Ratcliffe & Gang Chen & Paul A. Scuffham, 2014. "Australian Public Preferences for the Funding of New Health Technologies," Medical Decision Making, , vol. 34(5), pages 638-654, July.
    8. Soto, José R. & Adams, Damian C. & Escobedo, Francisco J., 2016. "Landowner attitudes and willingness to accept compensation from forest carbon offsets: Application of best–worst choice modeling in Florida USA," Forest Policy and Economics, Elsevier, vol. 63(C), pages 35-42.
    9. Julie Ratcliffe & Terry Flynn & Frances Terlich & Katherine Stevens & John Brazier & Michael Sawyer, 2012. "Developing Adolescent-Specific Health State Values for Economic Evaluation," PharmacoEconomics, Springer, vol. 30(8), pages 713-727, August.
    10. Soto, José R. & Escobedo, Francisco J. & Khachatryan, Hayk & Adams, Damian C., 2018. "Consumer demand for urban forest ecosystem services and disservices: Examining trade-offs using choice experiments and best-worst scaling," Ecosystem Services, Elsevier, vol. 29(PA), pages 31-39.
    11. Nicolas Krucien & Verity Watson & Mandy Ryan, 2017. "Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1-16, December.
    12. Julie Ratcliffe & Elisabeth Huynh & Katherine Stevens & John Brazier & Michael Sawyer & Terry Flynn, 2016. "Nothing About Us Without Us? A Comparison of Adolescent and Adult Health‐State Values for the Child Health Utility‐9D Using Profile Case Best–Worst Scaling," Health Economics, John Wiley & Sons, Ltd., vol. 25(4), pages 486-496, April.
    13. Hess, Stephane & Palma, David, 2019. "Apollo: A flexible, powerful and customisable freeware package for choice model estimation and application," Journal of choice modelling, Elsevier, vol. 32(C), pages 1-1.
    14. Melissa M. Kreye & Elizabeth F. Pienaar & José R. Soto & Damian C. Adams, 2017. "Creating Voluntary Payment Programs: Effective Program Design and Ranchers’ Willingness to Conserve Florida Panther Habitat," Land Economics, University of Wisconsin Press, vol. 93(3), pages 459-480.
    15. Balbontin, C. & Ortúzar, J. de D. & Swait, J.D., 2015. "A joint best–worst scaling and stated choice model considering observed and unobserved heterogeneity: An application to residential location choice," Journal of choice modelling, Elsevier, vol. 16(C), pages 1-14.
    16. Coast, Joanna & Flynn, Terry N. & Natarajan, Lucy & Sproston, Kerry & Lewis, Jane & Louviere, Jordan J. & Peters, Tim J., 2008. "Valuing the ICECAP capability index for older people," Social Science & Medicine, Elsevier, vol. 67(5), pages 874-882, September.
    17. Ellen M. Janssen & Jodi B. Segal & John F. P. Bridges, 2016. "A Framework for Instrument Development of a Choice Experiment: An Application to Type 2 Diabetes," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 9(5), pages 465-479, October.
    18. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    19. Terry N. Flynn & Elisabeth Huynh & Tim J. Peters & Hareth Al‐Janabi & Sam Clemens & Alison Moody & Joanna Coast, 2015. "Scoring the Icecap‐a Capability Instrument. Estimation of a UK General Population Tariff," Health Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 258-269, March.
    20. Joanna Coast & Elisabeth Huynh & Philip Kinghorn & Terry Flynn, 2016. "Complex Valuation: Applying Ideas from the Complex Intervention Framework to Valuation of a New Measure for End-of-Life Care," PharmacoEconomics, Springer, vol. 34(5), pages 499-508, May.
    21. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923.
    22. Hareth Al-Janabi & Terry N. Flynn & Joanna Coast, 2011. "Estimation of a Preference-Based Carer Experience Scale," Medical Decision Making, , vol. 31(3), pages 458-468, May.
    23. Xinyi Ng & John F. P. Bridges & Melissa M. Ross & Emily Frosch & Gloria Reeves & Charles E. Cunningham & Susan dosReis, 2017. "A Latent Class Analysis to Identify Variation in Caregivers’ Preferences for their Child’s Attention-Deficit/Hyperactivity Disorder Treatment: Do Stated Preferences Match Current Treatment?," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 10(2), pages 251-262, April.
    24. Sarrias, Mauricio & Daziano, Ricardo, 2017. "Multinomial Logit Models with Continuous and Discrete Individual Heterogeneity in R: The gmnl Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 79(i02).
    25. Huynh, Elisabeth & Coast, Joanna & Rose, John & Kinghorn, Philip & Flynn, Terry, 2017. "Values for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluation at end of life," Social Science & Medicine, Elsevier, vol. 189(C), pages 114-128.
    26. N. Flynn, Terry & J. Peters, Tim & Coast, Joanna, 2013. "Quantifying response shift or adaptation effects in quality of life by synthesising best-worst scaling and discrete choice data," Journal of choice modelling, Elsevier, vol. 6(C), pages 34-43.
    27. Axel C. Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Reed Johnson, 2016. "Experimental measurement of preferences in health and healthcare using best-worst scaling: an overview," Health Economics Review, Springer, vol. 6(1), pages 1-14, December.
    28. Susan dosReis & Xinyi Ng & Emily Frosch & Gloria Reeves & Charles Cunningham & John Bridges, 2015. "Using Best–Worst Scaling to Measure Caregiver Preferences for Managing their Child’s ADHD: A Pilot Study," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 8(5), pages 423-431, October.
    29. Kreye, Melissa M. & Adams, Damian C. & Escobedo, Francisco J. & Soto, José R., 2016. "Does policy process influence public values for forest-water resource protection in Florida?," Ecological Economics, Elsevier, vol. 129(C), pages 122-131.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
    2. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Osman, Ahmed M.Y. & Wu, Jing & He, Xiaoning & Chen, Gang, 2021. "Eliciting SF-6Dv2 health state utilities using an anchored best-worst scaling technique," Social Science & Medicine, Elsevier, vol. 279(C).
    2. Hajji, Assma & Trukeschitz, Birgit & Malley, Juliette & Batchelder, Laurie & Saloniki, Eirini & Linnosmaa, Ismo & Lu, Hui, 2020. "Population-based preference weights for the Adult Social Care Outcomes Toolkit (ASCOT) for service users for Austria: Findings from a best-worst experiment," Social Science & Medicine, Elsevier, vol. 250(C).
    3. Joanna Coast, 2019. "Assessing capability in economic evaluation: a life course approach?," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 779-784, August.
    4. Tatenda T Yemeke & Elizabeth E Kiracho & Aloysius Mutebi & Rebecca R Apolot & Anthony Ssebagereka & Daniel R Evans & Sachiko Ozawa, 2020. "Health versus other sectors: Multisectoral resource allocation preferences in Mukono district, Uganda," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-15, July.
    5. Lien Nguyen & Hanna Jokimäki & Ismo Linnosmaa & Eirini-Christina Saloniki & Laurie Batchelder & Juliette Malley & Hui Lu & Peter Burge & Birgit Trukeschitz & Julien Forder, 2022. "Valuing informal carers’ quality of life using best-worst scaling—Finnish preference weights for the Adult Social Care Outcomes Toolkit for carers (ASCOT-Carer)," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(3), pages 357-374, April.
    6. Jennifer A Whitty & Ruth Walker & Xanthe Golenko & Julie Ratcliffe, 2014. "A Think Aloud Study Comparing the Validity and Acceptability of Discrete Choice and Best Worst Scaling Methods," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-9, April.
    7. Nicolas Krucien & Verity Watson & Mandy Ryan, 2017. "Is Best–Worst Scaling Suitable for Health State Valuation? A Comparison with Discrete Choice Experiments," Health Economics, John Wiley & Sons, Ltd., vol. 26(12), pages 1-16, December.
    8. Denise Doiron & Hong Il Yoo, 2020. "Stated preferences over job characteristics: A panel study," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 53(1), pages 43-82, February.
    9. Soekhai, V. & Donkers, B. & Levitan, B. & de Bekker-Grob, E.W., 2021. "Case 2 best-worst scaling: For good or for bad but not for both," Journal of choice modelling, Elsevier, vol. 41(C).
    10. Huynh, Elisabeth & Coast, Joanna & Rose, John & Kinghorn, Philip & Flynn, Terry, 2017. "Values for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluation at end of life," Social Science & Medicine, Elsevier, vol. 189(C), pages 114-128.
    11. Qinxin Guo & Junyi Shen, 2019. "An Empirical Comparison Between Discrete Choice Experiment and Best-worst Scaling: A Case Study of Mobile Payment Choice," Discussion Paper Series DP2019-14, Research Institute for Economics & Business Administration, Kobe University.
    12. Ratcliffe, Julie & Huynh, Elisabeth & Chen, Gang & Stevens, Katherine & Swait, Joffre & Brazier, John & Sawyer, Michael & Roberts, Rachel & Flynn, Terry, 2016. "Valuing the Child Health Utility 9D: Using profile case best worst scaling methods to develop a new adolescent specific scoring algorithm," Social Science & Medicine, Elsevier, vol. 157(C), pages 48-59.
    13. Terry N. Flynn & Elisabeth Huynh & Tim J. Peters & Hareth Al‐Janabi & Sam Clemens & Alison Moody & Joanna Coast, 2015. "Scoring the Icecap‐a Capability Instrument. Estimation of a UK General Population Tariff," Health Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 258-269, March.
    14. Lancsar, Emily & Louviere, Jordan & Donaldson, Cam & Currie, Gillian & Burgess, Leonie, 2013. "Best worst discrete choice experiments in health: Methods and an application," Social Science & Medicine, Elsevier, vol. 76(C), pages 74-82.
    15. Brendan Mulhern & Richard Norman & Deborah J. Street & Rosalie Viney, 2019. "One Method, Many Methodological Choices: A Structured Review of Discrete-Choice Experiments for Health State Valuation," PharmacoEconomics, Springer, vol. 37(1), pages 29-43, January.
    16. Julie Ratcliffe & Terry Flynn & Frances Terlich & Katherine Stevens & John Brazier & Michael Sawyer, 2012. "Developing Adolescent-Specific Health State Values for Economic Evaluation," PharmacoEconomics, Springer, vol. 30(8), pages 713-727, August.
    17. Judith Dams & Elisabeth Huynh & Steffi Riedel-Heller & Margrit Löbner & Christian Brettschneider & Hans-Helmut König, 2021. "German tariffs for the ICECAP-Supportive Care Measure (ICECAP-SCM) for use in economic evaluations at the end of life," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 22(3), pages 365-380, April.
    18. Yoo, Hong Il & Doiron, Denise, 2013. "The use of alternative preference elicitation methods in complex discrete choice experiments," Journal of Health Economics, Elsevier, vol. 32(6), pages 1166-1179.
    19. Aizaki, Hideo & Fogarty, James, 2023. "R packages and tutorial for case 1 best–worst scaling," Journal of choice modelling, Elsevier, vol. 46(C).
    20. N. Flynn, Terry & J. Peters, Tim & Coast, Joanna, 2013. "Quantifying response shift or adaptation effects in quality of life by synthesising best-worst scaling and discrete choice data," Journal of choice modelling, Elsevier, vol. 6(C), pages 34-43.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:eejocm:v:32:y:2019:i:c:3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/journal-of-choice-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.