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Adopted

Adopted Children


Description

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?

Usage

Adopted

Format

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

Source

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.

References

Friendly, Michael (2010). HE Plots for Repeated Measures Designs. Journal of Statistical Software, 37(4), 1-40. URL https://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.

See Also

Examples

# 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")))

if(requireNamespace("rgl")){
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"))
	)

heplots

Visualizing Hypothesis Tests in Multivariate Linear Models

v1.3-8
GPL (>= 2)
Authors
John Fox [aut], Michael Friendly [aut, cre], Georges Monette [ctb], Phil Chalmers [ctb]
Initial release
2021-01-20

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