Description Usage Arguments Examples

View source: R/bootDominanceAnalysis.r

Bootstrap procedure as presented on Azen and Budescu (2003).
Provides the expected level of dominance of predictor *X_i* over *X_j*,
as the degree to which the pattern found on sample is reproduced on the
bootstrap samples.
Use `summary()`

to get a nice formatted data.frame

1 2 3 4 5 6 7 8 9 |

`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 |

`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). |

1 2 3 | ```
lm.1<-lm(Employed~.,longley)
da.boot<-bootDominanceAnalysis(lm.1,R=1000)
summary(da.boot)
``` |

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.