IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/gwck3.html
   My bibliography  Save this paper

On Group Comparisons with Logistic Regression Models

Author

Listed:
  • Kuha, Jouni
  • Mills, Colin

Abstract

It is widely believed that regression models for binary responses are problematic if we want to compare estimated coefficients from models for different groups or with different explanatory variables. This concern has two forms. The first arises if the binary model is treated as an estimate of a model for an unobserved continuous response, and the second when models are compared between groups which have different distributions of other causes of the binary response. We argue that these concerns are usually misplaced. The first of them is only relevant if the unobserved continuous response is really the subject of substantive interest. If it is, the problem should be addressed through better measurement of this response. The second concern refers to a situation which is unavoidable but unproblematic, in that causal effects and descriptive associations are inherently group-dependent and can be compared as long as they are correctly estimated.

Suggested Citation

  • Kuha, Jouni & Mills, Colin, 2017. "On Group Comparisons with Logistic Regression Models," SocArXiv gwck3, Center for Open Science.
    • Handle: RePEc:osf:socarx:gwck3
    DOI: 10.31219/osf.io/gwck3
    as

    Download full text from publisher

    File URL: https://osf.io/download/58e783f2b83f69024f4ff3a7/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/gwck3?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
    ---><---

    References listed on IDEAS

    as
    1. Jacob Marschak, 1959. "Binary Choice Constraints on Random Utility Indicators," Cowles Foundation Discussion Papers 74, Cowles Foundation for Research in Economics, Yale University.
    2. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387, September.
    3. Richard Williams, 2009. "Using Heterogeneous Choice Models to Compare Logit and Probit Coefficients Across Groups," Sociological Methods & Research, , vol. 37(4), pages 531-559, May.
    4. Imbens,Guido W. & Rubin,Donald B., 2015. "Causal Inference for Statistics, Social, and Biomedical Sciences," Cambridge Books, Cambridge University Press, number 9780521885881, September.
    5. Maarten Buis, 2015. "Logistic regression: Why we often can do what we think we can do," United Kingdom Stata Users' Group Meetings 2015 08, Stata Users Group.
    6. Richard Breen & Anders Holm & Kristian Bernt Karlson, 2014. "Correlations and Nonlinear Probability Models," Sociological Methods & Research, , vol. 43(4), pages 571-605, November.
    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. Gerhard Tutz, 2020. "Modelling heterogeneity: on the problem of group comparisons with logistic regression and the potential of the heterogeneous choice model," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(3), pages 517-542, September.

    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. Kuha, Jouni & Mills, Colin, 2018. "On group comparisons with logistic regression models," LSE Research Online Documents on Economics 84163, London School of Economics and Political Science, LSE Library.
    2. Jouni Kuha & Colin Mills, 2020. "On Group Comparisons With Logistic Regression Models," Sociological Methods & Research, , vol. 49(2), pages 498-525, May.
    3. Konrad Menzel, 2021. "Structural Sieves," Papers 2112.01377, arXiv.org, revised Apr 2022.
    4. Andrés Elberg & Pedro M. Gardete & Rosario Macera & Carlos Noton, 2019. "Dynamic effects of price promotions: field evidence, consumer search, and supply-side implications," Quantitative Marketing and Economics (QME), Springer, vol. 17(1), pages 1-58, March.
    5. Yusuke Narita, 2018. "Toward an Ethical Experiment," Cowles Foundation Discussion Papers 2127, Cowles Foundation for Research in Economics, Yale University.
    6. Funk, Patrick & Davis, Alex & Vaishnav, Parth & Dewitt, Barry & Fuchs, Erica, 2020. "Individual inconsistency and aggregate rationality: Overcoming inconsistencies in expert judgment at the technical frontier," Technological Forecasting and Social Change, Elsevier, vol. 155(C).
    7. Emerson Melo, 2021. "Learning in Random Utility Models Via Online Decision Problems," Papers 2112.10993, arXiv.org, revised Aug 2022.
    8. 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.
    9. Yusuke Narita, 2018. "Experiment-as-Market: Incorporating Welfare into Randomized Controlled Trials," Cowles Foundation Discussion Papers 2127r, Cowles Foundation for Research in Economics, Yale University, revised May 2019.
    10. Gregory S. Crawford & Nicola Pavanini & Fabiano Schivardi, 2018. "Asymmetric Information and Imperfect Competition in Lending Markets," American Economic Review, American Economic Association, vol. 108(7), pages 1659-1701, July.
    11. Kasy, Maximilian, 2023. "The Political Economy of AI: Towards Democratic Control of the Means of Prediction," SocArXiv x7pcy, Center for Open Science.
    12. David Muller & Emerson Melo & Ruben Schlotter, 2023. "A Distributionally Robust Random Utility Model," Papers 2303.05888, arXiv.org.
    13. Kiran Tomlinson & Johan Ugander & Austin R. Benson, 2021. "Choice Set Confounding in Discrete Choice," Papers 2105.07959, arXiv.org, revised Aug 2021.
    14. Wongprawmas, Rungsaran & Canavari, Maurizio, 2015. "Heterogeneity in consumer preferences for food safety lavel in Thailand," 143rd Joint EAAE/AAEA Seminar, March 25-27, 2015, Naples, Italy 202744, European Association of Agricultural Economists.
    15. Daniel Minh McCarthy & Elliot Shin Oblander, 2021. "Scalable Data Fusion with Selection Correction: An Application to Customer Base Analysis," Marketing Science, INFORMS, vol. 40(3), pages 459-480, May.
    16. Stefan Wager & Kuang Xu, 2021. "Experimenting in Equilibrium," Management Science, INFORMS, vol. 67(11), pages 6694-6715, November.
    17. Pennesi, Daniele, 2021. "Intertemporal discrete choice," Journal of Economic Behavior & Organization, Elsevier, vol. 186(C), pages 690-706.
    18. Axel Mühlbacher & Anika Kaczynski & Peter Zweifel & F. Johnson, 2015. "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.
    19. Wongprawmas, Rungsaran & Canavari, Maurizio, 2017. "Consumers’ willingness-to-pay for food safety labels in an emerging market: The case of fresh produce in Thailand," Food Policy, Elsevier, vol. 69(C), pages 25-34.
    20. Anning Hu & Feinian Chen, 2019. "Allocation of Eldercare Responsibilities Between Children and the Government in China: Does the Sense of Injustice Matter?," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 38(1), pages 1-25, February.

    More about this item

    Statistics

    Access and download statistics

    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:osf:socarx:gwck3. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.