plot_power

Simultaneously evaluate multiple ordinal outcome measures. Applied data analysts in particular are faced with uncertainty in choosing appropriate statistical tests for ordinal data. The included 'shiny' application allows users to simulate outcomes given different ordinal data distributions.

Pat Callahan

ordinalsimr

Compare Ordinal Endpoints Using Simulations

plot_power function

<dl><dt>df</dt>
<dd>a dataframe with p-values and a sample_size column</dd>
<dt>power_threshold</dt>
<dd>numeric. desired power threshold</dd>
<dt>ci_band</dt>
<dd>logical. whether to include a confidence interval band around the power estimate</dd></dl>

Arguments

Plot Test Power — plot_power

<dl>

<dt>df</dt>
<dd>a dataframe with p-values and a sample_size column</dd>


<dt>power_threshold</dt>
<dd>numeric. desired power threshold</dd>


<dt>ci_band</dt>
<dd>logical. whether to include a confidence interval band around the power estimate</dd>

</dl>

plot_power: Plot Test Power

Description

Usage

Value

Arguments