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# syn.bin_logit.r Synthetic grouped logistic regression
# Table 9.22: Hilbe, Negative Binomial Regression, 2 ed, Cambridge Univ Press
nobs <- 50000
x1 <- runif(nobs)
x2 <- runif(nobs)
d <- rep(1:5, each=10000, times=1)*100 # denominator
xb <- 2 + .75*x1 - 1.25*x2 # linear predictor; values
exb <- 1/(1+exp(-xb)) # fit; predicted prob
by <- rbinom(nobs, size = d, p = exb) # random binomial variate
dby <- d - by # denominator - numerator
gby <- glm(cbind(by,dby) ~ x1 + x2, family=binomial(link="logit"))
summary(gby) # displays model output
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