litters {DAAG} | R Documentation |
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.
litters
This data frame contains the following columns:
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.
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)