On this Picostat.com statistics page, you will find information about the lbw data set which pertains to lbw. The lbw data set is found in the COUNT R package. You can load the lbw data set in R by issuing the following command at the console data("lbw"). This will load the data into a variable called lbw. If R says the lbw data set is not found, you can try installing the package by issuing this command install.packages("COUNT") and then attempt to reload the data. If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the lbw R data set. The size of this file is about 4,955 bytes.
The data come to us from Hosmer and Lemeshow (2000). Called the low
birth weight (lbw) data, the response is a binary variable, low,
which indicates whether the birth weight of a baby is under 2500g
(low=1), or over (low=0).
A data frame with 189 observations on the following 10 variables.
1=low birthweight baby; 0=norml weight
1=history of mother smoking; 0=mother nonsmoker
categorical 1-3: 1=white; 2-=black; 3=other
age of mother: 14-45
weight (lbs) at last menstrual period: 80-250 lbs
number of false of premature labors: 0-3
1=history of hypertension; 0 =no hypertension
1=uterine irritability; 0 no irritability
number of physician visits in 1st trimester: 0-6
birth weight in grams: 709 - 4990 gr
lbw is saved as a data frame.
Count models can use ftv as a response variable, or convert it to grouped format
Hosmer, D and S. Lemeshow (2000), Applied Logistic Regression, Wiley
Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press
Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC
glmbwp <- glm(ftv ~ low + smoke + factor(race), family=poisson, data=lbw)
glmbwnb <- glm.nb(ftv ~ low + smoke + factor(race), data=lbw)
Dataset imported from https://www.r-project.org.