A Report On A Cox Model Essay

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A Cox model is a well-recognized statistical technique for exploring the relationship between the survival of a patient and several explanatory variables. 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. Interpreting a Cox model involves examining the coefficients for each explanatory variable. A positive regression coefficient for an explanatory variable means that the hazard for patient having a high positive value on that particular variable is high. Conversely, a negative regression coefficient implies a better prognosis for patients with higher values of that variable. Cox’s method does not assume any particular distribution for the survival times, but it rather assumes that the effects of the different variables on survival are constant over time and are additive in a particular scale [17]. The hazard function is the probability that an individual will experience an event (for example, death) within a small time interval, given that the individual has survived up to the beginning of the interval. In this model the unique effect of a per-unit increase in a variable or covariate is assumed to be multiplicative with respect to the hazard rate [18]. For example, taking a drug may halve one 's hazard rate for a stroke occurring, or, changing the material from which a
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