This function exclusively returns the Kaplan-Meier survival estimate and the corresponding time points.
It does not provide standard errors or any additional outputs
that are typically included with the <code>survfit()</code> function.

A collection of easy-to-use tools for regression analysis of survival data with a cure fraction proposed in Su et al. (2022) <doi:10.1177/09622802221108579>. The modeling framework is based on the Cox proportional hazards mixture cure model and the bounded cumulative hazard (promotion time cure) model. The pseudo-observations approach is utilized to assess covariate effects and embedded in the variable selection procedure.

Sy Han (Steven) Chiou

pseudoCure

A Pseudo-Observations Approach for Analyzing Survival Data with
a Cure Fraction

Chien-Lin  Su

Feng-Chang  Lin

km function

<dl><dt>time</dt>
<dd>A numeric vector for the observed survival times.</dd>
<dt>status</dt>
<dd>A numeric vector for the event indicator;
0 indicates right-censoring and 1 indicates events.</dd></dl>

Arguments

Kaplan-Meier estimate — km

<dl>

<dt>time</dt>
<dd>A numeric vector for the observed survival times.</dd>


<dt>status</dt>
<dd>A numeric vector for the event indicator;
0 indicates right-censoring and 1 indicates events.</dd>

</dl>

km: Kaplan-Meier estimate

Description

Usage

Value

Arguments

Examples