Height, weight, head circumference and puberty of 748 Dutch boys.
Format
A data frame with 748 rows on the following 9 variables:
age
Decimal age (0-21 years)
hgt
Height (cm)
wgt
Weight (kg)
bmi
Body mass index
hc
Head circumference (cm)
gen
Genital Tanner stage (G1-G5)
phb
Pubic hair (Tanner P1-P6)
tv
Testicular volume (ml)
reg
Region (north, east, west, south, city)
Details
Random sample of 10% from the cross-sectional data used to construct the
Dutch growth references 1997. Variables gen and phb are ordered
factors. reg is a factor.
Source
Fredriks, A.M,, van Buuren, S., Burgmeijer, R.J., Meulmeester JF,
Beuker, R.J., Brugman, E., Roede, M.J., Verloove-Vanhorick, S.P., Wit, J.M.
(2000) Continuing positive secular growth change in The Netherlands
1955-1997. Pediatric Research, 47, 316-323.
Fredriks, A.M., van Buuren, S., Wit, J.M., Verloove-Vanhorick, S.P. (2000).
Body index measurements in 1996-7 compared with 1980. Archives of
Disease in Childhood, 82, 107-112.
Examples
# create two imputed data sets
imp <- mice(boys, m=1, maxit=2)
z <- complete(imp, 1)
# create imputations for age <8yrs
plot(z$age, z$gen, col=mdc(1:2)[1+is.na(boys$gen)],
xlab = "Age (years)", ylab = "Tanner Stage Genital")
# figure to show that the default imputation method does not impute BMI
# consistently
plot(z$bmi,z$wgt/(z$hgt/100)^2, col=mdc(1:2)[1+is.na(boys$bmi)],
xlab = "Imputed BMI", ylab="Calculated BMI")
# also, BMI distributions are somewhat different
require(MASS)
oldpar <- par(mfrow=c(1,2))
truehist(z$bmi[!is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,
col=mdc(1),xlab="BMI observed")
truehist(z$bmi[is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,
col=mdc(2),xlab="BMI imputed")
par(oldpar)
# repair the inconsistency problem by passive imputation
meth <- imp$meth
meth["bmi"] <- "~I(wgt/(hgt/100)^2)"
pred <- imp$predictorMatrix
pred["hgt","bmi"] <- 0
pred["wgt","bmi"] <- 0
imp2 <- mice(boys, m=1, maxit=2, meth=meth, pred=pred)
z2 <- complete(imp2, 1)
# show that new imputations are consistent
plot(z2$bmi,z2$wgt/(z2$hgt/100)^2, col=mdc(1:2)[1+is.na(boys$bmi)],
ylab="Calculated BMI")
# and compare distributions
oldpar <- par(mfrow=c(1,2))
truehist(z2$bmi[!is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,col=mdc(1),
xlab="BMI observed")
truehist(z2$bmi[is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,col=mdc(2),
xlab="BMI imputed")
par(oldpar)