generate_stacked_data

Function to generate stacked data by the subgroups considered in the model.

Subgroup analyses are routinely performed in clinical trial
analyses. From a methodological perspective, two key issues of
subgroup analyses are multiplicity (even if only predefined subgroups
are investigated) and the low sample sizes of subgroups which lead to
highly variable estimates, see e.g. Yusuf et al (1991)
<doi:10.1001/jama.1991.03470010097038>. This package implements
subgroup estimates based on Bayesian shrinkage priors, see Carvalho et
al (2019) <https://proceedings.mlr.press/v5/carvalho09a.html>. In
addition, estimates based on penalized likelihood inference are
available, based on Simon et al (2011) <doi:10.18637/jss.v039.i05>.
The corresponding shrinkage based forest plots address the
aforementioned issues and can complement standard forest plots in
practical clinical trial analyses.

Isaac Gravestock

bonsaiforest

Shrinkage Based Forest Plots

Mar Vazquez Rabunal

Daniel Sabanés Bové

Marcel Wolbers

F. Hoffmann-La Roche AG 

generate_stacked_data function

<dl><dt>base_model</dt>
<dd>(<code>formula</code>) the formula of the basic model that is going
to be fitted. Depending on <code>resptype</code> it will be the formula corresponding
to a coxph model or to a glm model. In the case of "survival" a formula like
Surv(time, status) ~ trt would be expected and in the "binary" case a
formula like y ~ trt.</dd>
<dt>subgroup_model</dt>
<dd>(<code>formula</code>) the formula with all the subgroup
variables.</dd>
<dt>data</dt>
<dd>(<code>data frame</code>) the data frame with the variables.</dd>
<dt>resptype</dt>
<dd>(<code>string</code>) the type of data used. Can be "survival"
or "binary".</dd></dl>

Arguments

Generation of Stacked Data by Subgroups — generate_stacked_data

<dl>

<dt>base_model</dt>
<dd>(<code>formula</code>) the formula of the basic model that is going
to be fitted. Depending on <code>resptype</code> it will be the formula corresponding
to a coxph model or to a glm model. In the case of "survival" a formula like
Surv(time, status) ~ trt would be expected and in the "binary" case a
formula like y ~ trt.</dd>


<dt>subgroup_model</dt>
<dd>(<code>formula</code>) the formula with all the subgroup
variables.</dd>


<dt>data</dt>
<dd>(<code>data frame</code>) the data frame with the variables.</dd>


<dt>resptype</dt>
<dd>(<code>string</code>) the type of data used. Can be "survival"
or "binary".</dd>

</dl>

generate_stacked_data: Generation of Stacked Data by Subgroups

Description

Usage

Value

Arguments

Examples