get_tipping_points

Identifies the weights closest to tipping points for specified quantiles.

Tipping point analysis for clinical trials that employ Bayesian dynamic borrowing via robust meta-analytic predictive (MAP) priors. Further functions facilitate expert elicitation of a primary weight of the informative component of the robust MAP prior and computation of operating characteristics. Intended use is the planning, analysis and interpretation of extrapolation studies in pediatric drug development, but applicability is generally wider.

Christian Stock

tipmap

Tipping Point Analysis for Bayesian Dynamic Borrowing

Morten Dreher

Emma Torrini

 Boehringer Ingelheim Pharma GmbH & Co. KG

get_tipping_points function

<dl><dt>tipmap_data</dt>
<dd>A data frame created by <code>create_tipmap_data()</code>.</dd>
<dt>quantile</dt>
<dd>The quantile(s) of the tipping point. Possible values are 0.025, 0.05, 0.1, 0.2, 0.8, 0.9, 0.95 and 0.975.</dd>
<dt>null_effect</dt>
<dd>The null treatment effect. Defaults to 0.</dd></dl>

Arguments

Identify tipping point for a specific quantile. — get_tipping_points

<dl>

<dt>tipmap_data</dt>
<dd>A data frame created by <code>create_tipmap_data()</code>.</dd>


<dt>quantile</dt>
<dd>The quantile(s) of the tipping point. Possible values are 0.025, 0.05, 0.1, 0.2, 0.8, 0.9, 0.95 and 0.975.</dd>


<dt>null_effect</dt>
<dd>The null treatment effect. Defaults to 0.</dd>

</dl>

get_tipping_points: Identify tipping point for a specific quantile.

Description

Usage

Value

Arguments

See Also

Examples