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Abstract

Many important research questions involve regression models in which the dependent variable is censored or reported in intervals rather than as a numerical 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 fexible distributional forms. The treatment of heteroskedasticity is expanded 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 accommodatec with this method.

Keywords

st0766 gintreg gintregplot interval regression partially adaptive estimation intreg stintreg gb2fit gb2lfit generalized beta of the second kind heteroskedasticity

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gintreg: Generalized interval regression

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