dirttee-package {dirttee}R Documentation

DIstributional Regression for Times To EvEnt


This package includes regession methods for right-censored response variables. It allows for the estimation of distributional regression methods with semiparametric predictors, including, for example, nonlinear, spatial or random effects. The distribution of the response can be estimated with expectiles, quantiles and mode regression. Censored observations can be included with accelerated failure time models or inverse probability of censoring weights.


Package: dirttee
Type: Package
Version: 1.0-0
Date: 2022-08-15
License: GPL (>= 2)


Alexander Seipp, Fabian Otto-Sobotka
Carl von Ossietzky University Oldenburg

Maintainer: Alexander Seipp <alexander.seipp@uni-oldenburg.de>

Special thanks for their help go to Lisa Eilers and Florian Berger!

Partially funded by the German Research Foundation (DFG) grant SO1313/1-1, project 'Distributional Regression for Time-to-Event Data'.


Seipp A, Uslar V, Weyhe D, Timmer A, Otto-Sobotka F (2021) Weighted expectile regression for right-censored data Statistics in Medicine, 40(25), 5501-5520

Seipp A, Uslar V, Weyhe D, Timmer A, Otto-Sobotka F (2022) Flexible semiparametric mode regression for time-to-event data (under review)

See Also

expectreg, gamlss, flexsurv


c100 <- colcancer[1:100,]

#mode regression
reg <- modreg(Surv(logfollowup, death) ~ sex + LNE, data = c100)

#expectile regression
fit_exp <- expectreg.aft(Surv(logfollowup, death) ~ LNE, data = c100,smooth="f")
fit_expipc <- expectreg.ipc(Surv(logfollowup, death) ~ sex + LNE, data = c100)

#quantile regression
qu1 <- qureg.aft(Surv(logfollowup, death) ~ sex + LNE, data=c100, smooth="fixed")

[Package dirttee version 1.0.1 Index]