surr_rsq_ci

This function generates the interval measure of surrogate R-squared by bootstrap.

To assess and compare the models' goodness of fit, R-squared is one of the most
popular measures. For categorical data analysis, however, no universally adopted
R-squared measure can resemble the ordinary least square (OLS) R-squared for
linear models with continuous data. This package implement the surrogate R-squared
measure for categorical data analysis, which is proposed in the study of Dungang Liu,
Xiaorui Zhu, Brandon Greenwell, and Zewei Lin (2022) <doi:10.1111/bmsp.12289>. It
can generate a point or interval measure of the surrogate R-squared. It can also
provide a ranking measure of the percentage contribution of each variable to the
overall surrogate R-squared. This ranking assessment allows one to check the
importance of each variable in terms of their explained variance. This package can
be jointly used with other existing R packages for variable selection and model
diagnostics in the model-building process.

XiaoruiJeremy Zhu

SurrogateRsq

Goodness-of-Fit Analysis for Categorical Data using the
Surrogate R-Squared

Xiaorui (Jeremy) Zhu

Dungang Liu

Zewei Lin

Brandon Greenwell

surr_rsq_ci function

<dl><dt>surr_rsq</dt>
<dd>A object of class <code>"surr_rsq"</code> that is generated by the function <code>"surr_rsq"</code>.
It contains the following components: <code>surr_rsq</code>, <code>reduced_model</code>, <code>full_model</code>, and <code>data</code>.</dd>
<dt>alpha</dt>
<dd>The significance level alpha. The confidence level is 1-alpha.</dd>
<dt>B</dt>
<dd>The number of bootstrap replications.</dd>
<dt>...</dt>
<dd>Additional optional arguments.</dd></dl>

Arguments

A function to calculate the interval estimate of the surrogate R-squared measure — surr_rsq_ci

<dl>

<dt>surr_rsq</dt>
<dd>A object of class <code>"surr_rsq"</code> that is generated by the function <code>"surr_rsq"</code>.
It contains the following components: <code>surr_rsq</code>, <code>reduced_model</code>, <code>full_model</code>, and <code>data</code>.</dd>


<dt>alpha</dt>
<dd>The significance level alpha. The confidence level is 1-alpha.</dd>


<dt>B</dt>
<dd>The number of bootstrap replications.</dd>


<dt>...</dt>
<dd>Additional optional arguments.</dd>

</dl>

surr_rsq_ci: A function to calculate the interval estimate of the surrogate R-squared measure

Description

Usage

Value

Arguments

Examples