Statistical Methods in Medical Research

 

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This version was published on February 1, 2008
Statistical Methods in Medical Research, Vol. 17, No. 1, 53-73 (2008)
DOI: 10.1177/0962280207081240

Joint modelling of mixed outcome types using latent variables

Charles McCulloch

Division of Biostatistics, Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA, chuck{at}biostat.ucsf.edu

After a brief review of the use of latent variables to accommodate the correlation among multiple outcomes of mixed types, through theoretical and numerical calculation, the consequences of such a construction are quantified. The effects of including latent variables on marginal inference in these models are contrasted with the situation for jointly normal outcomes. A simulation study illustrates the efficiency and reduction in bias gains possible in using joint models, and analysis of an example from the field of osteoarthritis illustrates potential practical differences.


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