plot_distribution_results

This function takes a wide table of p-values (i.e. one column for each statistical test), converts it to long format, and creates a density plot of the p-values by each test.

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_distribution_results function

<dl><dt>df</dt>
<dd>data frame where each column is a set of p-values for a different statistical test</dd>
<dt>alpha</dt>
<dd>numeric. significance level</dd>
<dt>outlier_removal</dt>
<dd>numeric. set x-axis scale maximum by proportion</dd></dl>

Arguments

Plot Distribution — plot_distribution_results

<dl>

<dt>df</dt>
<dd>data frame where each column is a set of p-values for a different statistical test</dd>


<dt>alpha</dt>
<dd>numeric. significance level</dd>


<dt>outlier_removal</dt>
<dd>numeric. set x-axis scale maximum by proportion</dd>

</dl>

plot_distribution_results: Plot Distribution

Description

Usage

Value

Arguments