The Cox Proportional Hazards Model is a fundamental statistical technique widely used in the field of survival analysis, particularly in medical research. Developed by Sir David Cox in 1972, this model is designed and developed to analyze the relationship between the survival time of subjects and one or more predictor variables. Unlike traditional regression models, it does not require the specification of the underlying hazard function, making it a semi-parametric model. The important feature of the Cox Proportional Hazards Model is the proportional hazards assumption, which stipulates that the effect of the explanatory variables on the hazard is multiplicative and constant over time. This allows for the assessment of how different factors (like treatment methods or patient characteristics) are associated with the risk of a particular event, such as death or disease recurrence. The model’s flexibility and efficiency in handling censored data, where the outcome of interest is not observed for all subjects, make it a cornerstone tool in epidemiological studies and clinical trials.
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Cox, D. R. 1972. “Regression Models and Life-Tables.” Journal of the Royal Statistical Society: Series B (Methodological) 34 (2): 187–202. https://doi.org/10.1111/j.2517-6161.1972.tb00899.x