doll: Physician smoking and mortality count data

In msme: Functions and Datasets for "Methods of Statistical Model Estimation"

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))

msme documentation built on May 2, 2019, 5:07 a.m.