How can I fit a GLM using R's glm() evaluated at specific values (e.g. median)? -


i fit generalized linear model in r, using glm(). more precisely, it's nb.glm(). apparently, coefficients fitted in r packages deal generalized linear models evaluated @ mean values of other variables. there way evaluate coefficients holding values of other variables constant @ e.g. median or zero?

for example, example ucla's ats site on negbin regression:

require(foreign) require(ggplot2) require(mass) dat <- read.dta("http://www.ats.ucla.edu/stat/stata/dae/nb_data.dta") dat <- within(dat, {     prog <- factor(prog, levels = 1:3, labels = c("general", "academic", "vocational"))     id <- factor(id) }) summary(m1 <- glm.nb(daysabs ~ math + prog, data = dat)) 

the resulting coefficients evaluated @ mean value of daysabs, 5.96. find more intuitive evaluate coefficients @ median values.


Comments

Popular posts from this blog

c# - Validate object ID from GET to POST -

node.js - Custom Model Validator SailsJS -

php - Find a regex to take part of Email -