Central question how can we model separately dierent

Info iconThis preview shows page 1. Sign up to view the full content.

View Full Document Right Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: gression model? Central question: How can we model separately different factors that are likely to impact the observed event, so that we can isolate their individual effects? Heterogeneity: lives with very different characteristics (eg males and females, smokers and non-smokers) have different level of mortality. In other words, different factors (covariates) may have different effects on the risk. One method is to construct a model including the effects of the covariates on survival directly: a regression model. The most widely used regression model is the proportional hazards model (the Cox model) 3/45 Actuarial Statistics – Module 3: Semi-parametric methods: Cox Regression Model Introduction Covariates In many survival analysis problems, covariates are of the following types: Demographic / Societal (eg age, gender, education) Behavioral (eg smoking, physical activity level, alcohol) Physiological (eg blood pressure, heart rate) Covariates can be continuous measurements (weight) discrete measurements (age last birthday) indicators (1 for smoking, 0 for non-smoking) qualitative indicators (5 severe disease to 0 no symptoms) see K&M for a discussion of how to ‘code’ variables/factors 4/45 Actuarial Statistics – Module 3: Semi-parametric methods: Cox Regression Model Introduction Notation For the i th life we will denote the covariates (ris...
View Full Document

{[ snackBarMessage ]}

Ask a homework question - tutors are online