modeling data from Cases an controls

Dear Group: I have posed this question to a different list serve as well so apologize in advance if it is a duplicate message for some of you. I have sparse data (2-3 levels /patient) for a drug used in demographically similar patients with the same disease state but the disease in one group is treated (cases) and in the other is not (controls). My interest is to determine if there is a difference in the Population PK parameters because of different treatments 9i.e. determine the effect of treatment on drug PK). In analyzing these data, I developed 2 separate PK models -one for cases other for controls (both ran successfully) and generated population PK parameters. I then used a t test to determine if there was significant difference between the population parameters. When I sent this manuscript for publication it was rejected partly because I use 2 models. I now realize that perhaps I should be using one model and that using 2 separate models does not allow for good comparison of the groups. I have decided to integrate the data and develop only one model- how can I design the data file so that the cases and controls are recognized by the model. Is it appropriate to use: 'IF TYPE=1 THEN CASES' AND TYPE =2 THEN CONTROLS ETC. IS THERE A RESOURCE THAT DEMONSTRATES HOW TO DESIGN THE DATASET AND ALSO HOW ONE CAN DEVELOP THIS MODEL? does anyone have a sample data file and/or a model to share? Thanks in advance. Varsha Mehta, MS(CRDSA), Pharm.D., FCCP Clinical Associate Professor Pharmacy, Pediatrics and Communicable Diseases Clinical Pharmacist Neonatal Critical Care University of Michigan (O) 734-936-8985 (F) 734-936-6946 [email protected] ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues