Classical latent variable models for medical research

¹ Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA and Institute of Education, University of London, London, UK
² Department of Statistics and The Methodology Institute, London School of Economics, London, UK and Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway

^* To whom correspondence should be addressed.

	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 counselors’ interviews.