Cox model
- A Cox model is a well-recognised statistical technique for exploring the relationship between the survival of a patient and several explanatory variables.
- Survival analysis is concerned with studying the time between entry to a study and a subsequent event (such as death). Censored survival times occur if the event of interest does not occur for a patient during the study period.
- A Cox model provides an estimate of the treatment effect on survival after adjustment for other explanatory variables. It allows us to estimate the hazard (or risk) of death, or other event of interest, for individuals, given their prognostic variables.
- Even if the treatment groups are similar with respect to the variables known to effect survival, using the Cox model with these prognostic variables may produce a more precise estimate of the treatment effect (for example, by narrowing the confidence interval).
- Interpreting a Cox model involves examining the coefficients for each explanatory variable. A positive regression coefficient for an explanatory variable means that the hazard is higher, and thus the prognosis worse, for higher values. Conversely, a negative regression coefficient implies a better prognosis for patients with higher values
- of that variable.
Bandolier has available a longer essay on Cox models - 
What is a Cox model?