Application of multistate models in hospital epidemiology: Advances and challenges

被引：45

作者：

Beyersmann, Jan ^{[1
,2
]}

Wolkewitz, Martin ^{[1
,2
]}

Allignol, Arthur ^{[1
,2
]}

Grambauer, Nadine ^{[1
,2
]}

Schumacher, Martin ^{[2
]}

机构：

[1] Univ Freiburg, Freiburg Ctr Data Anal & Modelling, Freiburg, Germany

[2] Univ Med Ctr Freiburg, Inst Med Biometry & Med Informat, Freiburg, Germany

来源：

BIOMETRICAL JOURNAL | 2011年 / 53卷 / 02期

关键词：

Competing risks; Epidemic dynamics; Nosocomial infection; Sampling; Time-dependent bias; TIME-DEPENDENT BIAS; BLOOD-STREAM INFECTION; RISK-FACTOR ANALYSIS; CARE-UNIT STAY; LENGTH-OF-STAY; COMPETING RISKS; SUBDISTRIBUTION HAZARDS; NOSOCOMIAL INFECTION; BONE-MARROW; SURVIVAL;

D O I：

10.1002/bimj.201000146

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Survival analysis has established itself as a major statistical technique in medical research. Applications in hospital epidemiology, however, are only beginning to emerge. One reason for this delay is that usually complete follow-up of patients in hospital is feasible. This overview discusses where survival techniques provide additional insight into hospital epidemiology, and where they are, in fact, needed even in the absence of right-censoring.

引用

页码：332 / 350

页数：19

共 82 条

[1] What can statistics contribute to a causal understanding? [J].