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This version was published on February 1, 2008
Statistical Methods in Medical Research, Vol. 17, No. 1, 5-32 (2008)
DOI: 10.1177/0962280207081236

Classical latent variable models for medical research

Sophia Rabe-Hesketh

Graduate School of Education and Graduate Group in Biostatistics, University of California, Berkeley, USA, sophiarh{at}berkeley.edu, Institute of Education, University of London, London, UK

Anders Skrondal

Department of Statistics and The Methodology Institute, London School of Economics, London, UK, Division of Epidemiology, Norwegian Institute of Public Health, Oslo, Norway

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.


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