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tranSurv (version 1.2.2)

Transformation Model Based Estimation of Survival and Regression Under Dependent Truncation and Independent Censoring

Description

A latent, quasi-independent truncation time is assumed to be linked with the observed dependent truncation time, the event time, and an unknown transformation parameter via a structural transformation model. The transformation parameter is chosen to minimize the conditional Kendall's tau (Martin and Betensky, 2005) or the regression coefficient estimates (Jones and Crowley, 1992) . The marginal distribution for the truncation time and the event time are completely left unspecified. The methodology is applied to survival curve estimation and regression analysis.

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install.packages('tranSurv')

Monthly Downloads

76

Version

1.2.2

License

GPL (>= 3)

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Maintainer

Sy Chiou

Last Published

January 12th, 2021

Functions in tranSurv (1.2.2)

tranSurv-package

tranSurv:Transformation Model Based Survival Curve Estimation with Dependent Left Truncation
trSurvfit

Estimating survival curves via structural transformation model
trReg

Fitting regression model via structural transformation model
Surv

This is the Surv function imported from survival
gof

Goodness of fit based on left-truncated regression model
plot.trSurvfit

Plot the survival estimation based on the structural transformation model
trSurv.control

Auxiliary for Controlling trSurvfit Fitting
kendall

Kendall's tau
cKendall

Conditional Kendall's tau
wKendall

Weighted conditional Kendall's tau
pmcc

Product-Moment Correlation Coefficient