relrelimp {relimp} | R Documentation |
Produces a summary
of the relative importance of two predictors or two sets of predictors
in a fitted multinom
model object, and compares
relative importances
across two of the fitted logit models.
relrelimp(object, set1=NULL, set2=NULL, label1="set1", label2="set2", subset=TRUE, response.cat1=NULL, response.cat2=NULL)
object |
A model object of class
multinom |
set1 |
An index or vector of indices for the effects to be included in the numerator of the comparison |
set2 |
An index or vector of indices for the effects to be included in the denominator of the comparison |
label1 |
A character string; mnemonic name for the
variables in set1 |
label2 |
A character string; mnemonic name for the
variables in set2 |
subset |
Either a vector of numeric indices for the cases to be included
in the standardization of effects, or a vector of logicals
(TRUE for inclusion)
whose length is the same as the number of rows in the model frame,
object$model .
The default choice is to include all cases in the model frame. |
response.cat1 |
A character
string used to specify the first regression of interest
(i.e., the regression
which predicts the log odds on response.cat1 versus the model's
reference category). The response.cat1 argument should be an
element of object$lab . |
response.cat2 |
A character
string used to specify the second regression of interest
(i.e., the regression
which predicts the log odds on response.cat2 versus the model's
reference category). The response.cat2 argument should be an
element of object$lab . |
Computes a relative importance summary as described in
relimp
, for each of the two regressions specified by
response.cat1
and response.cat2
(relative to the same
reference category); and computes the
difference of those two relative importance summaries,
along with an estimated
standard error for that difference.
An object of class relrelimp
, with at least the following components:
model |
The call used to construct the model object summarized |
sets |
The two sets of indices specified as arguments |
response.category |
A character vector containing the specified
response.cat1 and response.cat2 |
log.ratio |
The natural logarithm of the ratio of effect
standard deviations corresponding to the two sets specified.
A vector with
three components: the first is for response.cat1
versus the reference
category, the second for response.cat2 versus the
reference category,
the third is the difference. |
se.log.ratio |
Estimated standard errors for the elements of
log.ratio |
David Firth, d.firth@warwick.ac.uk
## Data on housing and satisfaction, from Venables and Ripley library(MASS) library(nnet) data(housing) house.mult <- multinom(Sat ~ Infl + Type + Cont, weights = Freq, data = housing) relrelimp(house.mult, set1 = 2:3, set2 = 7, label1 = "Influence", label2 = "Contact", response.cat1 = "Medium", response.cat2 = "High") ## Computes the relative contribution of Influence and Contact in ## each of the two logistic regressions (Med/Low and High/Low), and ## compares those two relative-contribution measures.