Description Usage Format Source Examples
Data on the body and brain weights of 20 mice, together with the size of the litter. Two mice were taken from each litter size.
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This data frame contains the following columns:
litter size
body weight
brain weight
Wainright P, Pelkman C and Wahlsten D 1989. The quantitative relationship between nutritional effects on preweaning growth and behavioral development in mice. Developmental Psychobiology 22: 183-193.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | print("Multiple Regression - Example 6.2")
pairs(litters, labels=c("lsize\n\n(litter size)", "bodywt\n\n(Body Weight)",
"brainwt\n\n(Brain Weight)"))
# pairs(litters) gives a scatterplot matrix with less adequate labeling
mice1.lm <- lm(brainwt ~ lsize, data = litters) # Regress on lsize
mice2.lm <- lm(brainwt ~ bodywt, data = litters) #Regress on bodywt
mice12.lm <- lm(brainwt ~ lsize + bodywt, data = litters) # Regress on lsize & bodywt
summary(mice1.lm)$coef # Similarly for other coefficients.
# results are consistent with the biological concept of brain sparing
pause()
hat(model.matrix(mice12.lm)) # hat diagonal
pause()
plot(lm.influence(mice12.lm)$hat, residuals(mice12.lm))
print("Diagnostics - Example 6.3")
mice12.lm <- lm(brainwt ~ bodywt+lsize, data=litters)
oldpar <-par(mfrow = c(1,2))
bx <- mice12.lm$coef[2]; bz <- mice12.lm$coef[3]
res <- residuals(mice12.lm)
plot(litters$bodywt, bx*litters$bodywt+res, xlab="Body weight",
ylab="Component + Residual")
panel.smooth(litters$bodywt, bx*litters$bodywt+res) # Overlay
plot(litters$lsize, bz*litters$lsize+res, xlab="Litter size",
ylab="Component + Residual")
panel.smooth(litters$lsize, bz*litters$lsize+res)
par(oldpar)
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