Surv

is.Surv

<p>This function is imported from the <code>survival</code> package,
used to create survival objects to be fitted with <code>trReg()</code>
and <code>trSurvfit</code>. See <code><a rd-options="survival" href="/link/Surv?package=tranSurv&version=1.2.2&to=survival" data-mini-rdoc="survival::Surv">Surv</a></code> for the
documentation on <code>Surv</code>.</p>

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.

Sy  Chiou

tranSurv

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

Sy Han (Steven) Chiou

Jing Qian

Surv function

<p>This function is imported from the <code>survival</code> package,
used to create survival objects to be fitted with <code>trReg()</code>
and <code>trSurvfit</code>. See <code><a rd-options='survival' href='Surv'>Surv</a></code> for the
documentation on <code>Surv</code>.</p>

Surv: This is the `Surv` function imported from `survival`

Description

Arguments