auto_shapiro_raw

Generates a HTML table of raw data from a numerical variables of a dataframe.

Simplify bivariate and regression analyses by automating
result generation, including summary tables, statistical tests, and
customizable graphs. It supports tests for continuous and dichotomous
data, as well as stepwise regression for linear, logistic, and Firth
penalized logistic models. While not a substitute for tailored
analysis, 'BiVariAn' accelerates workflows and is expanding features
like multilingual interpretations of results.The methods for selecting
significant statistical tests, as well as the predictor selection in
prediction functions, can be referenced in the works of Marc Kery
(2003) <doi:10.1890/0012-9623(2003)84[92:NORDIG]2.0.CO;2> and Rainer
Puhr (2017) <doi:10.1002/sim.7273>.

José Andrés Flores-García

BiVariAn

Bivariate Automatic Analysis

Antonio Augusto Gordillo-Moscoso

Jhoselin Marian Castro-Rodriguez

auto_shapiro_raw function

<dl><dt>data</dt>
<dd>Data frame from which variables will be extracted.</dd>
<dt>flextableformat</dt>
<dd>Logical operator to indicate the output desired. Default is TRUE. When FALSE, function will return a dataframe format.</dd></dl>

Arguments

Author

Automatic Shapiro-Wilk test table — auto_shapiro_raw

<dl>

<dt>data</dt>
<dd>Data frame from which variables will be extracted.</dd>


<dt>flextableformat</dt>
<dd>Logical operator to indicate the output desired. Default is TRUE. When FALSE, function will return a dataframe format.</dd>

</dl>

auto_shapiro_raw: Automatic Shapiro-Wilk test table

Description

Usage

Value

Arguments

Author

Examples