# RPD -- Example 1.12 -- Rel. Risk-1 vs. Dust Exposure

rr.dust <- data.frame(dust = c(75, 100, 150, 350, 600, 900, 1300, 1650, 2250),
                      rr = c(1.1, 1.05, 0.97, 1.9, 1.83, 2.45, 3.7, 3.52, 4.16))

rr.dust <- transform(rr.dust, rr.m.1 = rr-1)

print(rr.dust)

rr.dust.model <- lm(rr.m.1 ~ dust - 1, data=rr.dust)
                                        # "- 1" removes the intercept

summary(rr.dust.model)
anova(rr.dust.model)
predict(rr.dust.model, se.fit=TRUE)
residuals(rr.dust.model)

plot(rr.m.1 ~ dust, pch=20, xlim=c(0,2400), ylim=c(-0.5,4), data=rr.dust)
abline(rr.dust.model)

# Approximation to confidence bands for the mean:
lines(rr.dust$dust, predict(rr.dust.model,interval="confidence")[,"lwr"], lty=2)
lines(rr.dust$dust, predict(rr.dust.model,interval="confidence")[,"upr"], lty=2)