boys {mice}R Documentation

Growth of Dutch boys

Description

Height, weight, head circumference and puberty of 748 Dutch boys.

Usage

data(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. http://www.stefvanbuuren.nl/publications/Continuing secular - Ped Res 2000.pdf

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. http://www.stefvanbuuren.nl/publications/Body index - ADC 2000.pdf

Examples


# create two imputed data sets
imp <- mice(boys, m=2)
z <- complete(imp, 1)

# create imputations for age <8yrs
plot(z$age, z$gen, col=c("blue","red")[1+is.na(boys$gen)])

# figure to show that the default imputation method does not impute BMI 
# consistently
plot(z$bmi,z$wgt/(z$hgt/100)^2, col=c("blue","red")[1+is.na(boys$bmi)],
 ylab="Calculated BMI")   

# also, BMI distributions are somewhat different
oldpar <- par(mfrow=c(1,2))
truehist(z$bmi[!is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,
 col="blue",xlab="BMI observed")
truehist(z$bmi[is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,
 col="red",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=2, meth=meth, pred=pred)
z2 <- complete(imp2, 1)

# show that new imputations are consistent
plot(z2$bmi,z2$wgt/(z2$hgt/100)^2, col=c("blue","red")[1+is.na(boys$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="blue",
 xlab="BMI observed")
truehist(z2$bmi[is.na(boys$bmi)],h=1,xlim=c(10,30),ymax=0.25,col="red",
 xlab="BMI imputed")
par(oldpar)


[Package mice version 2.11 Index]