British Doctors Smoking and Coronary Heart Disease
The problem is to investigate the impact of smoking tobacco among British doctors, refer Example 9.2.1 of Dobson. In the year 1951, a survey was sent across among all the British doctors asking them whether they smoked tobacco and their age group Age_Group. The data also collects the person-years Person_Years of the doctors in the respective age group. A follow-up after ten years reveals the number of deaths Deaths, the smoking group indicator Smoker_Cat.
data(bs1)
A data frame with 10 observations on the following 9 variables.
Age_Groupa factor variable of age group with levels 35-44 45-54 55-64 65-74 75-84
Age_Catslightly re-coded to extract variables with Age_Cat taking values 1-5 respectively for the age groups 35-44, 45-54, 55-64, 65-74, and 75-84
Age_Squaresquare of the variable Age_Cat
Smoker_Catthe smoking group indicator NO YES
Smoke_Inda numeric vector
Smoke_Agetakes the Age_Cat values for the smokers group and 0 for the non-smokers
Deathsa follow-up after ten years revealing the number of deaths
Person_Yearsthe number of deaths standardized to 100000
Deaths_Per_Lakh_Yearsa numeric vector
Dobson (2002)
Dobson, A. J. (1990-2002). An Introduction to Generalized Linear Models, 2e. Chapman & Hall/CRC.
library(MASS) data(bs1) BS_Pois <- glm(Deaths~Age_Cat+Age_Square+Smoke_Ind+Smoke_Age,offset= log(Person_Years),data=bs1,family='poisson') logLik(BS_Pois) summary(BS_Pois) with(BS_Pois, pchisq(null.deviance - deviance,df.null - df.residual,lower.tail = FALSE)) confint(BS_Pois)
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