rstandard.uRegress

Extracts standardized residuals from <code>uRegress</code> objects by relying on
functionality from the <code>stats</code> package.

A set of tools to streamline data analysis. Learning both R and introductory statistics at the same time can be challenging, and so we created 'rigr' to facilitate common data analysis tasks and enable learners to focus on statistical concepts. We provide easy-to-use interfaces for descriptive statistics, one- and two-sample inference, and regression analyses. 'rigr' output includes key information while omitting unnecessary details that can be confusing to beginners. Heteroscedasticity-robust ("sandwich") standard errors are returned by default, and multiple partial F-tests and tests for contrasts are easy to specify. A single regression function can fit both linear and generalized linear models, allowing students to more easily make connections between different classes of models.

Amy D Willis

rigr

Regression, Inference, and General Data Analysis Tools in R

Taylor Okonek

Charles J Wolock

Brian D Williamson

Scott S Emerson

Andrew J Spieker

Yiqun T Chen

Travis Y Hee Wai

James P Hughes

R Core Team 

Akhil S Bhel

Thomas Lumley

rstandard.uRegress function

<dl><dt>model</dt>
<dd>an object of class <code>uRegress</code>, as returned by
regress.</dd>
<dt>...</dt>
<dd>other arguments to pass to <code>residuals.uRegress</code></dd></dl>

Arguments

Extract standardized residuals from uRegress objects — rstandard.uRegress

<dl>

<dt>model</dt>
<dd>an object of class <code>uRegress</code>, as returned by
regress.</dd>


<dt>...</dt>
<dd>other arguments to pass to <code>residuals.uRegress</code></dd>

</dl>

Extract standardized residuals from <code>uRegress</code> objects

rstandard.uRegress: Extract standardized residuals from `uRegress` objects

Description

Usage

Value

Arguments