A comparison of two drop-out weighting schemes in the analysis of clustered data with categorical and continuous responses

A model previously proposed for analyzing clustered data with a bivariate d iscrete and continuous response jointly is extended to a model that jointly analyzes categorical and continuous responses. As well, two previously pro posed weighting schemes for generalized estimating equations that compensat e for drop-out effects are investigated for unbiasedness and efficiency rev ealing conditions under which one scheme can be less efficient and more sus ceptible to influential observations. The data set used for demonstration i s longitudinal, containing information on nests of young bass gathered over the life of the nest.