Multivariate logistic regression for data from complex surveys

Multivariate logistic regression, introduced by Glonek and McCullagh (1995) as a generalisation of logistic regression, is useful in the analysis of longitudinal data as it allows for dependent repeated observations of a categorical variable and for incomplete response profiles. We show how the method can be extended to deal with data from complex surveys and we illustrate it on data from the Swiss Labour Force Survey. The effect of the sampling weights on the parameter estimates and their standard errors is considered.