When the dependent or outcome variable is the survival data, the regression method applied is
Cox Regression builds a predictive model for time-to-event data. The model produces a survival function that predicts the probability that the event of interest has occurred at a given time t for given values of the predictor variables. The shape of the survival function and the regression coefficients for the predictors are estimated from observed subjects; the model can then be applied to new cases that have measurements for the predictor variables. Note that information from censored subjects, that is, those that do not experience the event of interest during the time of observation, contributes usefully to the estimation of the model. Ref :
Multiple linear regression analysis
Multiple logistic regression analysis
Cox regression analysis
None of the above
Biostatistics