mnlChange2: Average Effects for Multinomial Logistic Regression Models

In davidaarmstrong/damisc: Dave Armstrong's Miscellaneous Functions

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

mnlChange2(obj, varnames, data, diffchange = c("unit", "sd"), n = 1, 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.
n	Number of diffchange units to change.
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

Examples

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

davidaarmstrong/damisc documentation built on Oct. 1, 2023, 3:05 p.m.