S4BuysePower-model.tables

model.tables,S4BuysePower-method

Extract a summary of the results from the <code>powerBuyseTest</code> function.

methods

Implementation of the Generalized Pairwise Comparisons (GPC) as defined in Buyse (2010) <doi:10.1002/sim.3923> for complete observations, and extended in Peron (2018) <doi:10.1177/0962280216658320> to deal with right-censoring. GPC compare two groups of observations (intervention vs. control group) regarding several prioritized endpoints to estimate the probability that a random observation drawn from one group performs better/worse/equivalently than a random observation drawn from the other group. Summary statistics such as the net treatment benefit, win ratio, or win odds are then deduced from these probabilities. Confidence intervals and p-values are obtained based on asymptotic results (Ozenne 2021 <doi:10.1177/09622802211037067>), non-parametric bootstrap, or permutations. The software enables the use of thresholds of minimal importance difference, stratification, non-prioritized endpoints (O Brien test), and can handle right-censoring and competing-risks.

Brice Ozenne

BuyseTest

Generalized Pairwise Comparisons

Eva Cantagallo

William Anderson

Julien Peron

Johan Verbeeck

S4BuysePower-model.tables function

<dl><dt>x</dt>
<dd>output of <code>powerBuyseTest</code></dd>
<dt>type</dt>
<dd>[character] should a summary of the results (<code>"summary"</code>) or the raw results (<code>"raw"</code>) be output?</dd>
<dt>statistic</dt>
<dd>[character] statistic relative to which the power should be computed:
<code>"netBenefit"</code> displays the net benefit, as described in Buyse (2010) and Peron et al. (2016)),
<code>"winRatio"</code> displays the win ratio, as described in Wang et al. (2016),
<code>"mannWhitney"</code> displays the proportion in favor of the treatment (also called Mann-Whitney parameter), as described in Fay et al. (2018).
Default value read from <code>BuyseTest.options()</code>.</dd>
<dt>endpoint</dt>
<dd>[character vector] the endpoints to be displayed: must be the name of the endpoint followed by an underscore and then by the threshold.</dd>
<dt>order.Hprojection</dt>
<dd>[integer 1,2] the order of the H-project to be used to compute the variance of the net benefit/win ratio.</dd>
<dt>transformation</dt>
<dd>[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed.</dd></dl>

Arguments

Author

Extract Summary for Class "S4BuysePower" — S4BuysePower-model.tables

<dl>

<dt>x</dt>
<dd>output of <code>powerBuyseTest</code></dd>


<dt>type</dt>
<dd>[character] should a summary of the results (<code>"summary"</code>) or the raw results (<code>"raw"</code>) be output?</dd>


<dt>statistic</dt>
<dd>[character] statistic relative to which the power should be computed:
<code>"netBenefit"</code> displays the net benefit, as described in Buyse (2010) and Peron et al. (2016)),
<code>"winRatio"</code> displays the win ratio, as described in Wang et al. (2016),
<code>"mannWhitney"</code> displays the proportion in favor of the treatment (also called Mann-Whitney parameter), as described in Fay et al. (2018).
Default value read from <code>BuyseTest.options()</code>.</dd>


<dt>endpoint</dt>
<dd>[character vector] the endpoints to be displayed: must be the name of the endpoint followed by an underscore and then by the threshold.</dd>


<dt>order.Hprojection</dt>
<dd>[integer 1,2] the order of the H-project to be used to compute the variance of the net benefit/win ratio.</dd>


<dt>transformation</dt>
<dd>[logical] should the CI be computed on the logit scale / log scale for the net benefit / win ratio and backtransformed.</dd>

</dl>

S4BuysePower-model.tables: Extract Summary for Class "S4BuysePower"

Description

Usage

Value

Arguments

Author

See Also