COUNT (version 1.3.2)

lbwgrp: lbwgrp

Description

grouped format of the lbw data. The observation level data come to us form Hosmer and Lemeshow (2000). Grouping is such that lowbw is the numerator, and cases the denominator of a binomial model, or cases may be an offset to the count variable, lowbw. Birthweights under 2500g classifies a low birthweight baby.

Usage

data(lbwgrp)

Format

A data frame with 6 observations on the following 7 variables.

lowbw

Number of low weight babies per covariate pattern: 12-60

cases

Number of observations with same covariate pattern: 30-165

smoke

1=history of mother smoking; 0=mother nonsmoker

race1

(1/0): Caucasian

race2

(1/0): Black

race3

(1/0): Other

low

low birth weight (not valid variable in grouped format)

Source

Hosmer, D and S. Lemeshow (2000), Applied Logistic Regression, Wiley

Details

lbwgrp is saved as a data frame. Count models: count response=lowbt; offset=log(cases); Binary: binomial numerator= lowbt; binomial denominator=cases

References

Hilbe, Joseph M (2007, 2011), Negative Binomial Regression, Cambridge University Press Hilbe, Joseph M (2009), Logistic Regression Models, Chapman & Hall/CRC

Examples

data(lbwgrp)
glmgp <- glm(lowbw ~ smoke + race2 + race3 + offset(log(cases)), family=poisson, data=lbwgrp)
summary(glmgp)
exp(coef(glmgp))
library(MASS)
glmgnb <- glm.nb(lowbw ~  smoke + race2 + race3, data=lbwgrp)
summary(glmgnb)
exp(coef(glmgnb))