summary.partR2

Displays extended results of partR2, including R2,
part (semi-partial) R2, inclusive R2, structure coefficients and beta weights.

models

Partitioning the R2 of GLMMs into variation explained by each
predictor and combination of predictors using semi-partial (part) R2 and
inclusive R2. Methods are based on the R2 for GLMMs described in
Nakagawa & Schielzeth (2013) and Nakagawa, Johnson & Schielzeth (2017).

Martin A Stoffel

partR2

Partitioning R2 in GLMMs

Martin A. Stoffel

Shinichi Nakagawa

Holger Schielzeth

summary.partR2 function

<dl><dt>object</dt>
<dd>partR2 object returned from one of the partR2 functions</dd>
<dt>round_to</dt>
<dd>Defaults to 4 (decimals)</dd>
<dt>ests</dt>
<dd>Defaults to FALSE, if TRUE, also prints raw model estimates.</dd>
<dt>...</dt>
<dd>Additional arguments; not used at the moment</dd></dl>

Arguments

Complete summary of a partR2 object — summary.partR2

<dl>

<dt>object</dt>
<dd>partR2 object returned from one of the partR2 functions</dd>


<dt>round_to</dt>
<dd>Defaults to 4 (decimals)</dd>


<dt>ests</dt>
<dd>Defaults to FALSE, if TRUE, also prints raw model estimates.</dd>


<dt>...</dt>
<dd>Additional arguments; not used at the moment</dd>

</dl>

summary.partR2: Complete summary of a partR2 object

Description

Usage

Value

Arguments