effect_tabular

effect_odds_ratio

effect_relative_risk

effect_risk_difference

User can either use or extend these functions to configure effect calculation.

Create descriptive tables for continuous and categorical variables.
Apply summary statistics and counting function, with or without a grouping variable, and create beautiful reports using 'rmarkdown' or 'officer'.
You can also compute effect sizes and statistical tests if needed.

Dan Chaltiel

crosstable

Crosstables for Descriptive Analyses

David Hajage

effect_tabular function

<dl><dt>x</dt>
<dd>categorical vector (character, factor, ...)</dd>
<dt>by</dt>
<dd>categorical vector (of exactly 2 unique levels)</dd>
<dt>conf_level</dt>
<dd>confidence interval level</dd></dl>

Arguments

<ul>
<li><code>effect_odds_ratio()</code>: (Default) calculate the odds ratio</li>
<li><code>effect_relative_risk()</code>: calculate the relative risk</li>
<li><code>effect_risk_difference()</code>: calculate the risk difference</li>
</ul>

Functions

Author

Effect measure for association between two categorical variables — effect_tabular

<dl>

<dt>x</dt>
<dd>categorical vector (character, factor, ...)</dd>


<dt>by</dt>
<dd>categorical vector (of exactly 2 unique levels)</dd>


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

</dl>

effect_tabular: Effect measure for association between two categorical variables

Description

Usage

Value

Arguments

Functions

Author

See Also