The Stratified Cox Procedure

5 TheStratifiedCoxProcedure1731745. The Stratified Cox ProcedureIntroductionWe begin with an example of the use of the Stratified Coxprocedure for a single predictor that does not satisfy the PHassumption. We then describe the general approach for fittinga Stratified cox model , including the form of the (partial) like-lihood function used to estimate model also describe the assumption of no interaction that istypically incorporated into most computer programs thatcarry out the Stratified Cox Procedure . We show how the no-interaction assumption can be tested, and what can be doneif interaction is conclude with a second example of the Stratified Cox pro-cedure in which more than one variable is outline below gives the user a preview of the material tobe covered by the presentation. A detailed outline for reviewpurposes follows the (page 176) Example (pages 176 180) General Stratified Cox (SC) model (pages 180 181) No-Interaction Assumption and How to TestIt (pages 182 188) Second Example Involving Several StratificationVariables (pages 188 193) Graphical View of the Stratified Cox Approach(pages 193 194) (pages 195 196)Objectives175 ObjectivesUpon completing the chapter, the learner should be able to:1.

The “stratified Cox model” is a modification of the Cox proportional hazards (PH) model that allows for control by “stratification” of a predictor that does not satisfy the PH assumption. Predictors that are assumed to satisfy the PH assumption are included in the model, whereas the predictor be-ing stratified is not included.

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  Model, Hazards, Proportional, Cox model, Cox proportional hazards

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