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Confidence intervals for predicted outcomes in regression models for categorical outcomes

Author

Listed:
  • Jun Xu

    (Indiana University)

  • J. Scott Long

    (Indiana University)

Abstract

We discuss methods for computing confidence intervals for predictions and discrete changes in predictions for regression models for categorical outcomes. The methods include endpoint transformation, the delta method, and bootstrap- ping. We also describe an update to prvalue and prgen from the SPost package, which adds the ability to compute confidence intervals. The article provides several examples that illustrate the application of these methods. Copyright 2005 by StataCorp LP.

Suggested Citation

  • Jun Xu & J. Scott Long, 2005. "Confidence intervals for predicted outcomes in regression models for categorical outcomes," Stata Journal, StataCorp LP, vol. 5(4), pages 537-559, December.
  • Handle: RePEc:tsj:stataj:v:5:y:2005:i:4:p:537-559
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    References listed on IDEAS

    as
    1. Weihua Guan, 2003. "From the help desk: Bootstrapped standard errors," Stata Journal, StataCorp LP, vol. 3(1), pages 71-80, March.
    2. Tim Liao, 2000. "Estimated Precision for Predictions from Generalized Linear Models in Sociological Research," Quality & Quantity: International Journal of Methodology, Springer, vol. 34(2), pages 137-152, May.
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    Cited by:

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    2. Joshua Klugman & Jun Xu, 2008. "Racial Differences in Public Confidence in Education: 1974-2002," Social Science Quarterly, Southwestern Social Science Association, vol. 89(1), pages 155-176.
    3. Lei Chen, 2016. "Local Institutions, Audit Quality, and Corporate Scandals of US-Listed Foreign Firms," Journal of Business Ethics, Springer, vol. 133(2), pages 351-373, January.
    4. Quigley, Neil & Boyle, Glenn & Guthrie, Graeme, 2008. "Estimating Implied Valuation Parameters: Extension and Application to Ground Lease Rentals," Working Paper Series 4012, Victoria University of Wellington, The New Zealand Institute for the Study of Competition and Regulation.
    5. J. Scott Long, 2006. "Group comparisons and other issues in interpreting models for categorical outcomes using Stata," North American Stata Users' Group Meetings 2006 15, Stata Users Group.
    6. repec:eee:resene:v:50:y:2017:i:c:p:105-123 is not listed on IDEAS
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    8. repec:spr:qualqt:v:51:y:2017:i:3:d:10.1007_s11135-016-0334-1 is not listed on IDEAS
    9. Khoury, Theodore A. & Pleggenkuhle-Miles, Erin G., 2011. "Shared inventions and the evolution of capabilities: Examining the biotechnology industry," Research Policy, Elsevier, vol. 40(7), pages 943-956, September.
    10. Angermeyer, Matthias C. & Matschinger, Herbert & Link, Bruce G. & Schomerus, Georg, 2014. "Public attitudes regarding individual and structural discrimination: Two sides of the same coin?," Social Science & Medicine, Elsevier, vol. 103(C), pages 60-66.
    11. Ahearn, Mary Clare & El-Osta, Hisham & Mishra, Ashok K., 2013. "Considerations in Work Choices of U.S. Farm Households: The Role of Health Insurance," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 38(1), April.
    12. Botzen, W.J.W. & Bouwer, L.M. & van den Bergh, J.C.J.M., 2010. "Climate change and hailstorm damage: Empirical evidence and implications for agriculture and insurance," Resource and Energy Economics, Elsevier, vol. 32(3), pages 341-362, August.
    13. Lan, Jing & Munro, Alistair & Liu, Zhen, 2017. "Environmental regulatory stringency and the market for abatement goods and services in China," Resource and Energy Economics, Elsevier, vol. 50(C), pages 105-123.
    14. Schuknecht, Ludger & Martin, Reiner & Vansteenkiste, Isabel, 2007. "The role of the exchange rate for adjustment in boom and bust episodes," Working Paper Series 813, European Central Bank.

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