lmWithCov

Calculate regression coefficients and \(R^2\) for an OLS regression.
Could be used with <code>dominanceAnalysis</code> to
perform a dominance analysis without the original data.

Dominance analysis is a method that allows to compare the
relative importance of predictors in multiple regression models:
ordinary least squares, generalized linear models,
hierarchical linear models, beta regression and dynamic linear models.
The main principles and methods of
dominance analysis are described in
Budescu, D. V. (1993) <doi:10.1037/0033-2909.114.3.542> and
Azen, R., & Budescu, D. V. (2003) <doi:10.1037/1082-989X.8.2.129>
for ordinary least squares regression. Subsequently, the extensions
for multivariate regression, logistic regression and
hierarchical linear models were described in
Azen, R., & Budescu, D. V. (2006) <doi:10.3102/10769986031002157>,
Azen, R., & Traxel, N. (2009) <doi:10.3102/1076998609332754> and
Luo, W., & Azen, R. (2013) <doi:10.3102/1076998612458319>,
respectively.

Claudio Bustos Navarrete

dominanceanalysis

Dominance Analysis

Filipa Coutinho Soares

lmWithCov function

<dl><dt>f</dt>
<dd>formula for lm model</dd>
<dt>x</dt>
<dd>correlation/covariance matrix</dd></dl>

Arguments

Uses covariance/correlation matrix for calculate OLS — lmWithCov

<dl>

<dt>f</dt>
<dd>formula for lm model</dd>


<dt>x</dt>
<dd>correlation/covariance matrix</dd>

</dl>

lmWithCov: Uses covariance/correlation matrix for calculate OLS

Description

Usage

Value

Arguments

Examples