Average Effects for Multinomial Logistic Regression Models

Description

Calculates average effects of a variable in multinomial logistic regression holding all other variables at observed values.

Usage

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mnlChange2(obj, varnames, data, diffchange = c("unit", "sd"), R = 1500)

Arguments

obj

An object of class multinom

varnames

A string identifying the variable to be manipulated.

data

Data frame used to fit object.

diffchange

A string indicating the difference in predictor values to calculate the discrete change. sd gives plus and minus one-half standard deviation change around the median and unit gives a plus and minus one-half unit change around the median.

R

Number of simulations.

Value

A list with elements:

mean

Average effect of the variable for each category of the dependent variable.

lower

Lower 95 percent confidence bound

upper

Upper 95 percent confidence bound

Author(s)

Dave Armstrong (UW-Milwaukee, Department of Political Science)

Examples

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library(nnet)
data(france)
mnl.mod <- multinom(vote ~ age + male + retnat + lrself, data=france)
mnlChange2(mnl.mod, "lrself", data=france, )	

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