Байесовский подход к оцениванию факторов риска в анализе продолжительности жизни

This paper presents building regression model with supervised selectivity to be applied in survival analysis. Its basic characteristics are small number of observations and included censoring observations. Bayesian approach, where maximum likelihood criteria is set up based on the Cox proportional hazards model, is proposed for estimating the regression coefficients of the model. The suggested criteria can eliminate redundant factors and keep meaningful ones to analyze survival in research of patient group. The specific model has been tested and confirmed by simulation and real data.