Cox made pioneering and important contributions to numerous areas of statistics and applied probability, of which the best known are: •
Logistic regression, which is employed when the variable to be predicted is
categorical (i.e., can take a limited number of values, e.g., gender, race (in the US census)), binary (a special case of categorical with only two values - e.g., success/failure, disease/no disease), or
ordinal, where the categories can be ranked (e.g., pain intensity can be absent, mild, moderate, severe, unbearable). Cox's 1958 paper and further publications in the 1960s addressed the case of binary logistic regression. • The
proportional hazards model, which is widely used in the analysis of survival data, was developed by him in 1972. An example of the use of the proportional hazards model is in survival analysis in medical research. The model can be used in clinical trials to investigate time-based information about cohorts of patients, such as their response to exposure to certain chemical substances. • The
Cox process was named after him. ==Awards==