Transformation Model Based Estimation of Survival and Regression Under Dependent Truncation and Independent Censoring
Auxiliary for Controlling trSurvfit Fitting
Estimating survival curves via structural transformation model
Weighted conditional Kendall's tau
Conditional Kendall's tau
Goodness of fit based on left-truncated regression model
Kendall's tau
Plot the survival estimation based on the structural transformation mo...
Product-Moment Correlation Coefficient
This is the Surv function imported from survival
tranSurv:Transformation Model Based Survival Curve Estimation with Dep...
Fitting regression model via structural transformation model
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) <doi:10.1198/016214504000001538> or the regression coefficient estimates (Jones and Crowley, 1992) <doi:10.2307/2336782>. 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.