boys {mice} | R Documentation |
Height, weight, head circumference and puberty of 748 Dutch boys.
data(boys)
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)
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.
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
# 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)