title: Classical latent variable models for medical research.
abstract: 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.
authors.affiliation: Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, CA 94720-1670, USA. sophiarh@berkeley.edu
authors.forename: Sophia
authors.initials: S
authors.lastname: Rabe-Hesketh
authors.forename: Anders
authors.initials: A
authors.lastname: Skrondal
mesh_terms: D035843:Biomedical Research; D001699:Biometry; D005163:Factor Analysis, Statistical; D006801:Humans; D008137:Longitudinal Studies; D015201:Meta-Analysis as Topic; D015233:Models, Statistical; D010352:Patient Dropouts; D011788:Quality of Life; D016019:Survival Analysis