## Week 2: Classical Linear Regression Model
## Code from class

## regression example from Benoit and Marsh 2008 dataset

require(foreign)
dail <- read.dta("dail2002.dta")
mdl <- lm(votes1st ~ spend_total*incumb + minister, data=dail)
summary(mdl)

## code from class

yhat <- mdl$fitted.values   # uses the lm object mdl from previous
ybar <- mean(mdl$model[,1])
y <- mdl$model[,1]          # can't use dail$votes1st since diff N
SST <- sum((y-ybar)^2)
SSR <- sum((yhat-ybar)^2)
SSE <- sum((yhat-y)^2)
SSE
sum(mdl$residuals^2)
(r2 <- SSR/SST)
(adjr2 <- (1 - (1-r2)*(462-1)/(462-4-1)))
summary(mdl)$r.squared      # note the call to summary()
SSE/457
sqrt(SSE/457)
summary(mdl)$sigma