doll {msme} | R Documentation |
Physician smoking and mortality count data
Description
The data are a record of physician smoking habits and the frequency of death by myocardial infarction, or heart attack.
Usage
data(doll)
Format
A data frame with 10 observations on the following variables.
- age
Ordinal age group
- smokes
smoking status
- deaths
count of deaths in category
- pyears
number of physisian years in scope of data
- a1
Dummy variable for age level 1
- a2
Dummy variable for age level 2
- a3
Dummy variable for age level 3
- a4
Dummy variable for age level 4
- a5
Dummy variable for age level 5
Details
The physicians were divided into five age divisions, with deaths as the response, person years (pyears) as the binomial denominator, and both smoking behavior (smokes) and agegroup (a1–a5) as predictors.
Source
Doll, R and A.B.Hill (1966). Mortality of British doctors in relation to smoking; observations on coronary thrombosis. In Epidemiological Approaches to the Study of Cancer and Other Chronic Diseases, W. Haenszel (ed), 19: 204–268. National Cancer Institute Monograph.
References
Hilbe, J., and A.P. Robinson. 2012. Methods of Statistical Model Estimation. Chapman & Hall / CRC.
Examples
data(doll)
i.glog <- irls(deaths ~ smokes + ordered(age),
family = "binomial",
link = "logit",
data = doll,
m = doll$pyears)
summary(i.glog)
glm.glog <- glm(cbind(deaths, pyears - deaths) ~
smokes + ordered(age),
data = doll,
family = binomial)
coef(summary(glm.glog))