Modelling multivariate survival data is complicated by the complex association structure among responses. To balance model flexibility and interpretability, we propose a semiparametric copula to modulate data, with marginal distributions of response components described linear transformation models. conduct inference about parameters, develop two-stage maximum likelihood method three-stage pseu...

Abstract The survival energy model (SEM) is a recently introduced novel approach to mortality prediction, which offers cohort-wise distribution function of the time death as first hitting “survival energy” diffusion process zero. In this study, we propose SEM that can serve suitable candidate in family prediction models. We also proposed method improve an earlier work. further examine practical...

background: multifactorial regression models are frequently used in medicine to estimate survival rate of patients across risk groups. however, their results are not generalisable, if in the development of models assumptions required are not satisfied.  missing data is a common problem in pathology. the aim of this paper is to address the danger of exclusion of cases with missing data, and to h...