infants {osDesign} | R Documentation |
Individual-level infant mortality data on 235,272 births in the U.S. state of North Carolina, in 2003 and 2004.
data(infants)
A data frame consisting of 235,464 observations, with the following columns:
year
Year of birth; either 2003 or 2004.
race
A 9-level categorical variable indicating the race of the baby. See Details, below.
male
A binary variable; 0=female; 1=male.
mage
Age of the mother, years.
weeks
Number of completed weeks of gestation.
cignum
Average number of cigarettes. A value of ‘98’ indicates smoking but unknown amount.
gained
Weight gained during pregnancy, lbs.
weight
Birth weight, grams.
death
A binary variable indicating death within 1st year of life; 0=alive; 1=death.
The data were compiled by the North Carolina State Center for Health Statistics (http://www.irss.unc.edu/).
The race
variable is coded as follows:
0 = Other non-white
1 = White
2 = Black
3 = American Indian
4 = Chinese
5 = Japanese
6 = Hawaiin
7 = Filipino
8 = Other Asian or Pacific Islander
## Code to generate an aggregated dataset ## ## Not run: data(infants) ## infants$smoker <- as.numeric(infants$cignum > 0) infants$teen <- as.numeric(infants$mage < 20) infants$lowgain <- as.numeric(infants$gained < 20) infants$early <- as.numeric(infants$weeks < 32) infants$lbw <- as.numeric(infants$weight < 2500) ## listAgg <- list(year=infants$year, smoker=infants$smoker, teen=infants$teen, lowgain=infants$lowgain, race=infants$race, male=infants$male, early=infants$early, lbw=infants$lbw) infantsAgg <- aggregate(rep(1, nrow(infants)), listAgg, FUN=sum) names(infantsAgg)[ncol(infantsAgg)] <- "N" infantsAgg$Y <- aggregate(infants$death, listAgg, FUN=sum)$x ## End(Not run)