door_cumulative_forestplot

Generate cumulative DOOR forest plot

Statistical methods and related graphical representations for the Desirability of Outcome Ranking (DOOR) methodology. The DOOR is a paradigm for the design, analysis, interpretation of clinical trials and other research studies based on the patient centric benefit risk evaluation. The package provides functions for generating summary statistics from individual level/summary level datasets, conduct DOOR probability-based inference, and visualization of the results. For more details of DOOR methodology, see Hamasaki and Evans (2025) <doi:10.1201/9781003390855>. For more explanation of the statistical methods and the graphics, see the technical document and user manual of the DOOR 'Shiny' apps at <https://methods.bsc.gwu.edu>.

Yijie He

door

Analysis of Clinical Trials with the Desirability of Outcome
Ranking Methodology

Qihang Wu

Toshimitsu Hamasaki

door_cumulative_forestplot function

<dl><dt>y1, y2</dt>
<dd>Numeric vectors of DOOR proportion or frequency distribution for group 1, group 2.
The entries should be ordered from most desirable to least desirable</dd>
<dt>n1, n2</dt>
<dd>Sample sizes of group 1, group 2; must be specified if method = "prop"</dd>
<dt>data_type</dt>
<dd>Either "freq" for frequency input or "prop" for proportion input
when using y1 and y2</dd>
<dt>summary_obj</dt>
<dd>An object returned by <code>individual_to_summary()</code>; Alternative
input for y1 and y2</dd>
<dt>conf_level</dt>
<dd>confidence level</dd>
<dt>ci_method</dt>
<dd>methods for calculating confidence interval</dd></dl>

Arguments

Generate cumulative DOOR forest plot — door_cumulative_forestplot

<dl>

<dt>y1, y2</dt>
<dd>Numeric vectors of DOOR proportion or frequency distribution for group 1, group 2.
The entries should be ordered from most desirable to least desirable</dd>


<dt>n1, n2</dt>
<dd>Sample sizes of group 1, group 2; must be specified if method = "prop"</dd>


<dt>data_type</dt>
<dd>Either "freq" for frequency input or "prop" for proportion input
when using y1 and y2</dd>


<dt>summary_obj</dt>
<dd>An object returned by <code>individual_to_summary()</code>; Alternative
input for y1 and y2</dd>


<dt>conf_level</dt>
<dd>confidence level</dd>


<dt>ci_method</dt>
<dd>methods for calculating confidence interval</dd>

</dl>

door_cumulative_forestplot: Generate cumulative DOOR forest plot

Description

Usage

Value

Arguments

Examples