dominanceanalysis (version 2.0.0)

bootAverageDominanceAnalysis: Bootstrap average values for Dominance Analysis

Description

Bootstrap average values and correspond standard errors for each predictor in the dominance analysis. Those values are used for general dominance.

Usage

bootAverageDominanceAnalysis(
  x,
  R,
  constants = c(),
  terms = NULL,
  fit.functions = "default",
  null.model = NULL,
  ...
)

Arguments

x

lm, glm or lmer model

R

number on bootstrap resamples

constants

vector of predictors to remain unchanged between models. i.e. vector of variables not subjected to bootstrap analysis.

terms

vector of terms to be analyzed. By default, obtained from the model

fit.functions

list of functions which provides fit indices for model. See fit.functions param in dominanceAnalysis function.

null.model

only for linear mixed models, null model against to test the submodels. i.e. only random effects, without any fixed effect.

...

Other arguments provided to lm or lmer (not implemented yet).

Details

Use summary() to get a nice formatted data.frame object.

Examples

# NOT RUN {
lm.1<-lm(Employed~.,longley)
da.ave.boot<-bootAverageDominanceAnalysis(lm.1,R=1000)
summary(da.ave.boot)
# }