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A Report On A Cox Model

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A Cox model is a statistical method used for exploring the relationship between the survival of a patient and several risk variables. A Cox model provides an estimate of the therapeutic procedure effect on survival after adjustment for other explanatory variables. It allows to estimate the risk of mortality, or other events of interest, for patients, given their prognostic variables. Cox model analysis involves examining the coefficients for each 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 negative values of that variable. Cox’s method does not assume a 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 at some level or scale [17]. The hazard function is the probability that an individual will experience an event (like mortality) within some 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 is assumed to be multiplicative with respect to the hazard rate [18]. For example, following a certain therapeutic procedure may reduce one 's hazard rate for mortality by one half. Thus in order to convert this multiplicative problem to additive we tend

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