using-fit-indices

original.model

newdata

Null model, only needed for HLM models.

null.model

Required if only a covariance/correlation matrix is provided.

base.cov

<code><a rd-options="" href="/link/dominanceAnalysis?package=dominanceanalysis&version=2.0.0" data-mini-rdoc="dominanceanalysis::dominanceAnalysis">dominanceAnalysis</a></code> tries to infer, based on the class of the
model provided, the appropriate fit indices, using the scheme
da.CLASS.fit for name. This method has two interfaces, one for retrieving
the names of the fit indices, and another to retrieve the indices based
on the 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

using-fit-indices function

<code><a rd-options='' href='dominanceAnalysis'>dominanceAnalysis</a></code> tries to infer, based on the class of the
model provided, the appropriate fit indices, using the scheme
da.CLASS.fit for name. This method has two interfaces, one for retrieving
the names of the fit indices, and another to retrieve the indices based
on the data.

using-fit-indices: Provides fit indices for different regression models.

Description

Arguments

Details