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Latent variable models for mixed categorical and survival responses, with an application to fertility preferences and family planning in Bangladesh

Department of Statistics, Athens University of Economics and Business, Athens, Greece, moustaki{at}aueb.gr

Fiona Steele

Centre for Multilevel Modelling, Graduate School of Education, University of Bristol, Bristol, UK

In this article, we discuss a latent variable model with continuous latent variables for manifest variables that are a mixture of categorical and survival outcomes. Models for censored and uncensored survival data are discussed. The model allows for covariate effects both on the manifest variables (direct effects) and on the latent variable(s) (indirect effects). The methodological developments are motivated by a demographic application: an exploration of women’s fertility preferences and family planning behaviour in Bangladesh.

Key Words: latent variable models • mixed response data • structural equation modelling • survival analysis

Statistical Modelling, Vol. 5, No. 4, 327-342 (2005)
DOI: 10.1191/1471082X05st100oa


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