draw_cluster_bootstrap

This function is part of the cluster bootstrap optimism correction
procedure described in Signorelli et al. (2021). Note 
that the function does not perform the random sampling, but it
extracts the correct records from a dataframe, given the ids of
the sampled clusters (subjects)

internal

Computes penalized regression calibration (PRC), a
statistical method for the dynamic prediction of survival when many
longitudinal predictors are available. See Signorelli (2024)
<doi:10.32614/RJ-2024-014> and Signorelli et al. (2021)
<doi:10.1002/sim.9178> for details.

Mirko Signorelli

pencal

Penalized Regression Calibration (PRC) for the Dynamic
Prediction of Survival

Pietro Spitali

Roula Tsonaka

Barbara Vreede

draw_cluster_bootstrap function

<dl><dt>df</dt>
<dd>a data frame in long format</dd>
<dt>idvar</dt>
<dd>name of the subject id in <code>df</code> (it should be a
numeric id that ranges from 1 to n, without skipping values)</dd>
<dt>boot.ids</dt>
<dd>identifiers of the subjects to be sampled</dd></dl>

Arguments

Author

Draw a cluster bootstrap sample from a data frame in long format — draw_cluster_bootstrap

<dl>

<dt>df</dt>
<dd>a data frame in long format</dd>


<dt>idvar</dt>
<dd>name of the subject id in <code>df</code> (it should be a
numeric id that ranges from 1 to n, without skipping values)</dd>


<dt>boot.ids</dt>
<dd>identifiers of the subjects to be sampled</dd>

</dl>

draw_cluster_bootstrap: Draw a cluster bootstrap sample from a data frame in long format

Description

Usage

Value

Arguments

Author

References