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Gologit2: Generalized Logistic Regression Models for Ordinal Dependent Variables

Author

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  • Richard Williams

    (Sociology Dept, University of Notre Dame)

Abstract

-gologit2- is a user-written program that estimates generalized logistic regression models for ordinal dependent variables. The actual values taken on by the dependent variable are irrelevant except that larger values are assumed to correspond to "higher" outcomes. A major strength of -gologit2- is that it can also estimate two special cases of the generalized model: the proportional odds model and the partial proportional odds model. Hence, -gologit2- can estimate models that are less restrictive than the proportional odds/parallel lines models estimated by –ologit- (whose assumptions are often violated) but more parsimonious and interpretable than those estimated by a non-ordinal method, such as multinomial logistic regression. The –autofit- option greatly simplifies the process of identifying partial proportional odds models that fit the data. Two alternative but equivalent parameterizations of the model that have appeared in the literature are both supported. Other key advantages of -gologit2- include support for linear constraints, Stata 8.2 survey data (svy) estimation, and the computation of estimated probabilities via the –predict- command. -gologit2- is inspired by Vincent Fu’s –gologit- program and is backward compatible with it but offers several additional powerful options.

Suggested Citation

  • Richard Williams, 2005. "Gologit2: Generalized Logistic Regression Models for Ordinal Dependent Variables," North American Stata Users' Group Meetings 2005 21, Stata Users Group.
    • Handle: RePEc:boc:asug05:21
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    Cited by:

    1. Ziwen Ling & Christopher R. Cherry & John H. MacArthur & Jonathan X. Weinert, 2017. "Differences of Cycling Experiences and Perceptions between E-Bike and Bicycle Users in the United States," Sustainability, MDPI, vol. 9(9), pages 1-18, September.
    2. Andrews, Matthew R., 2009. "Isomorphism and the Limits to African Public Financial Management Reform," Scholarly Articles 4415942, Harvard Kennedy School of Government.
    3. Dilek Yıldız & Hilal Arslan & Alanur Çavlin, 2021. "Understanding women’s well-being in Turkey," Vienna Yearbook of Population Research, Vienna Institute of Demography (VID) of the Austrian Academy of Sciences in Vienna, vol. 19(1), pages 255-291.
    4. Ivonne Honekamp, 2012. "Financial Literacy and Retirement Savings in Germany," NFI Working Papers 2012-WP-03, Indiana State University, Scott College of Business, Networks Financial Institute.
    5. Jiang, Jing & Wu, Shanhong, 2022. "The effects of cash-holding motivation on cash management dynamics," Research in International Business and Finance, Elsevier, vol. 59(C).
    6. Aida Isabel Tavares & Pedro Lopes Ferreira, 2020. "Public satisfaction with health system coverage, empirical evidence from SHARE data," International Journal of Health Economics and Management, Springer, vol. 20(3), pages 229-249, September.
    7. Seden Akcinaroglu & Efe Tokdemir, 2018. "To instill fear or love: Terrorist groups and the strategy of building reputation," Conflict Management and Peace Science, Peace Science Society (International), vol. 35(4), pages 355-377, July.
    8. Alison Reynolds & Claire E. Altman, 2018. "Subjective Health Assessments Among Older Adults in Mexico," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 37(5), pages 825-850, October.
    9. Zakir Husain & Swagata Sarkar, 2011. "Gender Disparities in Educational Trajectories in India: Do Females Become More Robust at Higher Levels?," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 101(1), pages 37-56, March.
    10. Daniel Wheatley & Craig Bickerton, 2019. "Measuring changes in subjective well-being from engagement in the arts, culture and sport," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(3), pages 421-442, September.

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