#‘— #’ title: “Framingham example” #’ author: “Szu-Yu Chen” #’ date: 21 September 2020 #’—

file location

fL<-"https://math.montana.edu/shancock/data/Framingham.txt"

#
dta <- read.table(fL, header=T)

# recode gender variable
dta$sex <- factor(dta$sex, 
                  levels=c(1, 2), 
                  labels=c("M", "F")) 

# lattice plot
library(lattice)
xyplot(sbp ~ dbp | sex, 
       data=dta, cex=.5,
       type=c("p","g","r"),
       xlab="Diastolic pressure (mmHg)",
       ylab="Systolic pressure (mmHg)")

#
m0 <- lm(sbp ~ dbp, data=dta)

#
m1 <- lm(sbp ~ dbp + sex, data=dta)

#
m2 <- lm(sbp ~ dbp + sex + sex:dbp, data=dta)

#
anova(m0, m1, m2)

## Analysis of Variance Table
## 
## Model 1: sbp ~ dbp
## Model 2: sbp ~ dbp + sex
## Model 3: sbp ~ dbp + sex + sex:dbp
##   Res.Df    RSS Df Sum of Sq      F    Pr(>F)    
## 1   4697 941778                                  
## 2   4696 927853  1     13925 71.800 < 2.2e-16 ***
## 3   4695 910543  1     17310 89.256 < 2.2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

#
plot(rstandard(m2) ~ fitted(m2), 
     cex=.5, 
     xlab="Fitted values", 
     ylab="Standardized residuals")
grid()

# The end