# Selected Forbes 500 Companies by Sector -- Homogeneity of Regressions

# Data Source:  DASL (Forbes 500 Companies Sales)

companies <- read.table("companies.dat", header=TRUE)

  # character variable Sector is automatically converted to a factor

companies <- transform(companies, logSales = log(Sales),
                                  logAssets = log(Assets))


model1 <- lm(logSales ~ logAssets*Sector, data=companies)

model2 <- lm(logSales ~ logAssets + Sector, data=companies)

model3 <- lm(logSales ~ logAssets, data=companies)


anova(model2, model1)  # equal slopes?

anova(model3, model2)  # equal intercepts (given equal slopes)?

anova(model3, model1)  # equal slopes and intercepts?


# Plot of regressions by group:

png("companies.png", 1024, 768)  # create PNG figure file in current directory

plot(logSales ~ logAssets, col=as.integer(Sector), pch=as.integer(Sector),
     cex=2, cex.lab=1.5, cex.main=2,
     main="Forbes 500 Companies -- Homogeneity of Regressions", data=companies)

with(companies, legend("topleft", legend=levels(Sector), col=1:nlevels(Sector),
                       pch=1:nlevels(Sector), cex=2))

for(i in 1:nlevels(companies$Sector)){
  abline(lm(logSales ~ logAssets, subset=(as.integer(Sector)==i),
            data=companies), col=i)
}

dev.off()  # close figure file