Mahal

model

pred

number of Mahal values to print (highest values). Default is 10

values

Compute Mahalanobis Distance for Multiple Regression

Provides squared semi partial correlations, tolerance, Mahalanobis, Likelihood Ratio Chi Square, and Pseudo R Square. Aberson, C. L. (2022) <doi:10.31234/osf.io/s2yqn>.

Chris Aberson

BetterReg

Better Statistics for OLS and Binomial Logistic Regression

Mahal function

<dl><dt>model</dt>
<dd>name of model</dd>
<dt>pred</dt>
<dd>number of predictors</dd>
<dt>values</dt>
<dd>number of Mahal values to print (highest values). Default is 10</dd></dl>

Arguments

Compute Mahalanobis Distance for Multiple Regression — Mahal

<dl>

<dt>model</dt>
<dd>name of model</dd>


<dt>pred</dt>
<dd>number of predictors</dd>


<dt>values</dt>
<dd>number of Mahal values to print (highest values). Default is 10</dd>

</dl>

Mahal: Compute Mahalanobis Distance for Multiple Regression

Description

Usage

Value

Arguments

Examples