Illness-death model: statistical perspective and differential equations

被引：13

作者：

Brinks, Ralph ^{[1
]}

Hoyer, Annika ^{[2
]}

机构：

[1] Univ Hosp Duesseldorf, Hiller Res Unit Rheumatol, Dusseldorf, Germany

[2] German Diabet Ctr, Inst Epidemiol & Biometry, Dusseldorf, Germany

来源：

LIFETIME DATA ANALYSIS | 2018年 / 24卷 / 04期

关键词：

Fix-Neyman competing risks model; Illness-death model; Multistate models; Non-parametric estimation of transition rates; Incidence; Prevalence; Markov processes; Kolmogorov Differential Equations; AGE-SPECIFIC INCIDENCE; PREVALENCE; DISEASES;

D O I：

10.1007/s10985-018-9419-6

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

The aim of this work is to relate the theory of stochastic processes with the differential equations associated with multistate (compartment) models. We show that the Kolmogorov Forward Differential Equations can be used to derive a relation between the prevalence and the transition rates in the illness-death model. Then, we prove mathematical well-definedness and epidemiological meaningfulness of the prevalence of the disease. As an application, we derive the incidence of diabetes from a series of cross-sections.

引用

页码：743 / 754

页数：12

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