assign_groups

(Brief description of the function here.)

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

assign_groups function

<dl><dt>sample_size</dt>
<dd>total number of people under observation.</dd>
<dt>sample_prob</dt>
<dd>a vector of probability weights for obtaining the elements of the vector being sampled.</dd>
<dt>prob0</dt>
<dd>vector probability of each possible outcome for the null group</dd>
<dt>prob1</dt>
<dd>vector probability of each possible outcome for the intervention group</dd>
<dt>seed</dt>
<dd>integer specifying the seed number</dd>
<dt>.rng_kind</dt>
<dd>seeding info passed to withr::with_seed</dd>
<dt>.rng_normal_kind</dt>
<dd>seeding info passed to withr::with_seed</dd>
<dt>.rng_sample_kind</dt>
<dd>seeding info passed to withr::with_seed</dd></dl>

Arguments

Randomly assign groups — assign_groups

<dl>

<dt>sample_size</dt>
<dd>total number of people under observation.</dd>


<dt>sample_prob</dt>
<dd>a vector of probability weights for obtaining the elements of the vector being sampled.</dd>


<dt>prob0</dt>
<dd>vector probability of each possible outcome for the null group</dd>


<dt>prob1</dt>
<dd>vector probability of each possible outcome for the intervention group</dd>


<dt>seed</dt>
<dd>integer specifying the seed number</dd>


<dt>.rng_kind</dt>
<dd>seeding info passed to withr::with_seed</dd>


<dt>.rng_normal_kind</dt>
<dd>seeding info passed to withr::with_seed</dd>


<dt>.rng_sample_kind</dt>
<dd>seeding info passed to withr::with_seed</dd>

</dl>

assign_groups: Randomly assign groups

Description

Usage

Value

Arguments