osDesign (version 1.8)

infants: Infant mortality data from North Carolina

Description

Individual-level infant mortality data on 235,272 births in the U.S. state of North Carolina, in 2003 and 2004.

Usage

data(infants)

Format

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.

Details

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

Examples

# NOT RUN {
## Code to generate an aggregated dataset
##
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
# }