esoph {datasets} | R Documentation |
Data from a case-control study of (o)esophageal cancer in Ile-et-Vilaine, France.
esoph
A data frame with records for 88 age/alcohol/tobacco combinations.
[,1] | "agegp" | Age group | 1 25–34 years |
2 35–44 | |||
3 45–54 | |||
4 55–64 | |||
5 65–74 | |||
6 75+ | |||
[,2] | "alcgp" | Alcohol consumption | 1 0–39 gm/day |
2 40–79 | |||
3 80–119 | |||
4 120+ | |||
[,3] | "tobgp" | Tobacco consumption | 1 0– 9 gm/day |
2 10–19 | |||
3 20–29 | |||
4 30+ | |||
[,4] | "ncases" | Number of cases | |
[,5] | "ncontrols" | Number of controls |
Thomas Lumley
Breslow, N. E. and Day, N. E. (1980) Statistical Methods in Cancer Research. 1: The Analysis of Case-Control Studies. IARC Lyon / Oxford University Press.
require(stats) require(graphics) # for mosaicplot summary(esoph) ## effects of alcohol, tobacco and interaction, age-adjusted model1 <- glm(cbind(ncases, ncontrols) ~ agegp + tobgp * alcgp, data = esoph, family = binomial()) anova(model1) ## Try a linear effect of alcohol and tobacco model2 <- glm(cbind(ncases, ncontrols) ~ agegp + unclass(tobgp) + unclass(alcgp), data = esoph, family = binomial()) summary(model2) ## Re-arrange data for a mosaic plot ttt <- table(esoph$agegp, esoph$alcgp, esoph$tobgp) ttt[ttt == 1] <- esoph$ncases tt1 <- table(esoph$agegp, esoph$alcgp, esoph$tobgp) tt1[tt1 == 1] <- esoph$ncontrols tt <- array(c(ttt, tt1), c(dim(ttt),2), c(dimnames(ttt), list(c("Cancer", "control")))) mosaicplot(tt, main = "esoph data set", color = TRUE)