RE: Missing Gender (Categorical values)

From:"Stephen Duffull" Subject: RE: [NMusers] Missing Gender (Categorical values) Date:Wed, 31 Jul 2002 08:55:00 +1000 Hi Just my 2c worth. I have tried joint function modelling on one data set - where about 50% of the patients had missing covariates. The covariates were continuous - rather than categorical. There weren't any other covariates to try and get an idea about the missing one in question (which is again different from your example)... so it was a matter of estimating the missing covariate and parameter values simultaneously from the PK data (there was a lot of that). Anyway it seemed to work ok - but we had difficulties due to the large proportion of missing covariates. With 70% of your sex data missing this could be problematic also. In addition, we did not find a satisfactory way of assessing the statistical significance of covariate relationships. When using joint function modelling the objective function is greatly inflated with estimating the covariates, which means that a simple LRT is not straightforward to perform. Regards Steve ***************************************** Stephen Duffull School of Pharmacy University of Queensland Brisbane 4072 Australia Tel +61 7 3365 8808 Fax +61 7 3365 1688 http://www.uq.edu.au/pharmacy/duffull.htm