Classical latent variable models for medical research

被引：104

作者：

Rabe-Hesketh, Sophia ^{[1
,2
,3
]}

Skrondal, Anders ^{[4
,5
,6
]}

机构：

[1] Univ Calif Berkeley, Grad Sch Educ, Berkeley, CA 94720 USA

[2] Univ Calif Berkeley, Grad Grp Biostat, Berkeley, CA 94720 USA

[3] Univ London, Inst Educ, London WC1N 1AZ, England

[4] London Sch Econ, Methodol Inst, London WC2A 2AE, England

[5] London Sch Econ, Dept Stat, London WC2A 2AE, England

[6] Norwegian Inst Publ Hlth, Div Epidemiol, Oslo, Norway

来源：

STATISTICAL METHODS IN MEDICAL RESEARCH | 2008年 / 17卷 / 01期

关键词：

D O I：

10.1177/0962280207081236

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Latent variable models are commonly used in medical statistics, although often not referred to under this name. In this paper we describe classical latent variable models such as factor analysis, item response theory, latent class models and structural equation models. Their usefulness in medical research is demonstrated using real data. Examples include measurement of forced expiratory flow, measurement of physical disability, diagnosis of myocardial infarction and modelling the determinants of clients' satisfaction with counsellors' interviews.

引用

页码：5 / 32

页数：28

共 139 条

[1] HETEROGENEITY IN SURVIVAL ANALYSIS [J].