Adopted | R Documentation |

## 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?

### 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

### Details

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?

### 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, M. (2010). HE Plots for Repeated Measures Designs.
*Journal of Statistical Software*, 37(4), 1-40.
doi:10.18637/jss.v037.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

`ex1605`

### 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
print(linearHypothesis(Adopted.mod, c("AMED","BMIQ")), SSP=FALSE)
# show separate linear regressions
op <- par(mfcol=c(2,4), mar=c(4,4,1,1)+.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)))
car::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"))
)
```