Life Tables with Concomitant Information

A regression model for the analysis of survival data adjusting for concomitant information is developed. The model presented can lead to the log linear exponential model (Glasser [1967]) and the life table regression model of Cox [1972]. In addition, the model described can be used to analyze data from the commonly employed actuarial life table. A discussion of the special case where one is comparing two survival curves is presented. The methods developed are illustrated using data from a clinical trial investigating treatments for lung cancer.

Keywords

Biometry, Lung Neoplasms, Linear regression; mixed models, Statistics as Topic, Models, Biological, Applications of statistics to biology and medical sciences; meta analysis, Life Expectancy, Humans, Regression Analysis, Mortality, General biology and biomathematics, Follow-Up Studies

Impact byBIP!

	selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	158
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 1%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 0.1%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%