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- W4205532366 abstract "Doubly truncated variables may be also involved in a regression setting. This chapter considers the case of a doubly truncated response variable X and a vector of covariates Z, which may be categorical or numerical, continuous or discrete. As a distinct feature from classical regression models, it analyzes the effect of the random double truncation in the observational bias. The chapter presents two types of regression models: Cox proportional hazards model and the accelerated failure time (AFT) model. The AFT regression model is often introduced as a log-linear regression model. The AFT model has been more traditionally used in the fully parametric setting in which the error distribution is specified. Nonparametric regression estimators with covariates of higher dimension may converge slowly, and their application requires caution. The chapter presents the code for reproducing the examples dealing with regression problems." @default.
- W4205532366 created "2022-01-25" @default.
- W4205532366 date "2022-01-14" @default.
- W4205532366 modified "2023-09-27" @default.
- W4205532366 title "Regression Analysis" @default.
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- W4205532366 doi "https://doi.org/10.1002/9781119500469.ch4" @default.
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