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gintreg: Generalized interval regression

Author

Listed:
  • James B. McDonald

    (Brigham Young University)

  • Jacob Triplett

    (University of North Carolina)

Abstract

Many important research questions involve regression models in which the dependent variable is censored or reported in intervals rather than as a nu- merical value. A common approach to treating these problems is to assume that the data correspond to a certain distribution (for example, a normal distribution) and then apply maximum likelihood estimation. While this method is widely used in the literature, it can yield inconsistent estimators in the presence of either heteroskedasticity or distributional misspecification. The gintreg command is a partially adaptive maximum-likelihood estimation procedure that 1) generalizes the intreg command by relaxing the normality assumption and 2) draws from a library of flexible distributional forms. The treatment of heteroskedasticity is ex- panded to account for possible skewness and kurtosis. Additional options provide interaction with the estimation process, informative metrics, and visualizations. Right- and left-censored, interval, grouped, and point data can be accommodated with this method.

Suggested Citation

  • James B. McDonald & Jacob Triplett, 2025. "gintreg: Generalized interval regression," Stata Journal, StataCorp LLC, vol. 25(1), pages 51-76, March.
    • Handle: RePEc:tsj:stataj:v:25:y:2025:i:1:p:51-76
    DOI: 10.1177/1536867X251322961
    Note: to access software from within Stata, net describe http://www.stata-journal.com/software/sj25-1/st766/
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