Missing value when modeling categorical data

Dear NMUsers, I am modeling ordered-categorical PD data versus time, but since the clinical trial is ongoing, I don't currently have complete data set for each subject. In other words, for some subjects, I have 1 year's PD data, but for some others, I can only collect PD data for 1 month. For the 1 month's case, it is like missing data for the rest of time. But I need to consider time course of the proportion of subjects who got a certain PD score. In my case, if I use the general logistic regression model to fit the relationship between time and proportions of event, would there be any problem? If so, how can I avoid it? Or need I consider censoring like survival analysis? Any suggestion would be appreciated very much. Thanks in advance, Tianli ***************************************************************** Tianli Wang University of Minnesota