Adopted: Adopted Children
In heplots: Visualizing Hypothesis Tests in Multivariate Linear Models

Description Usage Format Source References See Also Examples

Data are a subset from an observational, longitudinal, study on adopted children. Is child's intelligence related to intelligence of the biological mother and the intelligence of the adoptive mother?

The child's intelligence was measured at age 2, 4, 8, and 13 for this sample. How does intelligence change over time, and how are these changes related to intelligence of the birth and adoptive mother?

Adopted

A data frame with 62 observations on the following 6 variables.

AMED: adoptive mother's years of education (proxy for her IQ)
BMIQ: biological mother's score on IQ test
Age2IQ: IQ of child at age 2
Age4IQ: IQ of child at age 4
Age8IQ: IQ of child at age 8
Age13IQ: IQ of child at age 13

Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.

This data set is identical to ex1605 in the Sleuth2 package.

Friendly, Michael (2010). HE Plots for Repeated Measures Designs. Journal of Statistical Software, 37(4), 1-40. URL http://www.jstatsoft.org/v37/i04/.

Skodak, M. and Skeels, H.M. (1949). A Final Follow-up Study of One Hundred Adopted Children, Journal of Genetic Psychology 75: 85–125.

ex1605

# Treat as multivariate regression problem
Adopted.mod <- lm(cbind(Age2IQ, Age4IQ, Age8IQ, Age13IQ) ~ AMED + BMIQ, data=Adopted)
Adopted.mod

require(car)
# test overall multivariate regression
linearHypothesis(Adopted.mod, c("AMED","BMIQ"))

# show separate linear regressions
op <- par(mfcol=c(2,4), mar=c(4,4,2,2)+.1)
for (i in 3:6) {
	dataEllipse(as.matrix(Adopted[,c(1,i)]),col="black", levels=0.68, ylim=c(70,140))
	abline(lm(Adopted[,i] ~ Adopted[,1]), col="red", lwd=2)
	dataEllipse(as.matrix(Adopted[,c(2,i)]),col="black", levels=0.68, ylim=c(70,140))
	abline(lm(Adopted[,i] ~ Adopted[,2]), col="red", lwd=2)
	abline(a=0,b=1, lty=1, col="blue")
}
par(op)

# between-S (MMReg) plots
heplot(Adopted.mod, hypotheses=list("Reg"=c("AMED", "BMIQ")),
	main="IQ scores of adopted children: MMReg")

pairs(Adopted.mod, hypotheses=list("Reg"=c("AMED", "BMIQ")))

heplot3d(Adopted.mod, hypotheses=list("Reg"=c("AMED", "BMIQ")),
	col = c("red", "blue", "black", "gray"), wire=FALSE)

# Treat IQ at different ages as a repeated measure factor
# within-S models & plots
Age <- data.frame(Age=ordered(c(2,4,8,13)))
Anova(Adopted.mod, idata=Age, idesign=~Age, test="Roy")

# within-S plots
heplot(Adopted.mod, idata=Age, idesign=~Age, iterm="Age",
	cex=1.25, cex.lab=1.4, fill=c(FALSE, TRUE),
	hypotheses=list("Reg"=c("AMED", "BMIQ"))
	)