SimA100

The data were simulated as described in Blanche &amp; Eriksson (2023), using scenario A with sample size n=100.

datasets

Computation of t-year survival probabilities and t-year
risks with right censored survival data. The Kaplan-Meier estimator
is used to provide estimates for data without competing risks and
the Aalen-Johansen estimator is used when there are competing risks.
Confidence intervals and p-values are obtained using either usual
Wald-type inference or empirical likelihood inference, as described
in Thomas and Grunkemeier (1975) <doi:10.1080/01621459.1975.10480315>
and Blanche (2020) <doi:10.1007/s10985-018-09458-6>. Functions for
both one-sample and two-sample inference are provided. Unlike Wald-type
inference, empirical likelihood inference always leads to consistent
conclusions, in terms of statistical significance, when comparing
two risks (or survival probabilities) via either a ratio or a difference.

Paul Blanche

timeEL

Time to Event Analysis via Empirical Likelihood Inference

Frank Eriksson

SimA100 function

A data frame with 100 rows and 3 variables:<dl>
<dt>time</dt>
<dd>time to event</dd><dt>status</dt>
<dd>event status, 1 is main event, 2 is competing event, 0 is censored.</dd><dt>group</dt>
<dd>group (1 or 0)</dd>
</dl>

Format

Simulated competing risks data — SimA100

A data frame with 100 rows and 3 variables:<dl>
<dt>time</dt>
<dd>time to event</dd>

<dt>status</dt>
<dd>event status, 1 is main event, 2 is competing event, 0 is censored.</dd>

<dt>group</dt>
<dd>group (1 or 0)</dd>


</dl>

SimA100: Simulated competing risks data

Description

Usage

Arguments

Format

References