anova_glm

The function anova_glm() returns the Chi^2 and degrees of freedom for each variable &amp; the same was anova.rms() does from lrm() in the rms package.

Assessing the comparative performance of two logistic regression models or results of such models or classification models. Discrimination metrics include Integrated Discrimination Improvement (IDI), Net Reclassification Improvement (NRI), and difference in Area Under the Curves (AUCs), Brier scores and Brier skill. Plots include Risk Assessment Plots, Decision curves and Calibration plots. Methods are described in Pickering and Endre (2012) <doi:10.1373/clinchem.2011.167965> and Pencina et al. (2008) <doi:10.1002/sim.2929>.

Daniel Perez Vicencio

raptools

Risk Assessment Plot and Reclassification Metrics

John W Pickering

Dimitrios Doudesis

anova_glm function

<dl><dt>f</dt>
<dd>A logistic regression fit created using glm (base package)</dd></dl>

Arguments

The function anova_glm() returns the Chi^2 and degrees of freedom for each variable &amp; the same was anova.rms() does from lrm() in the rms package. — anova_glm

<dl>

<dt>f</dt>
<dd>A logistic regression fit created using glm (base package)</dd>

</dl>

anova_glm: The function anova_glm() returns the Chi^2 and degrees of freedom for each variable & the same was anova.rms() does from lrm() in the rms package.

Description

Usage

Value

Arguments