door_ci

This is a wrapper function for all CI calculation functions

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_ci 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>summary_obj</dt>
<dd>A object returned by <code>individual_to_summary()</code>; Alternative
input for y1 and y2</dd>
<dt>conf_level</dt>
<dd>Confidence level</dd>
<dt>data_type</dt>
<dd>Either "freq" for frequency input or "prop" for proportion input
when using y1 and y2</dd>
<dt>ci_method</dt>
<dd>One of "all" for all available methods, "halperin" for Halperin et al. (1989)'s
method, "ps_h" for pseudo-score approach for Halperin's method, "tanh" for inverse
hyperbolc tangent transformed method</dd>
<dt>...</dt>
<dd>Additional parameters passed for calculating pseudo-score type confidence interval</dd></dl>

Arguments

Calculate confidence intervals for DOOR probability — door_ci

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


<dt>conf_level</dt>
<dd>Confidence level</dd>


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


<dt>ci_method</dt>
<dd>One of "all" for all available methods, "halperin" for Halperin et al. (1989)'s
method, "ps_h" for pseudo-score approach for Halperin's method, "tanh" for inverse
hyperbolc tangent transformed method</dd>


<dt>...</dt>
<dd>Additional parameters passed for calculating pseudo-score type confidence interval</dd>

</dl>

door_ci: Calculate confidence intervals for DOOR probability

Description

Usage

Value

Arguments

See Also

Examples