Has anyone had experience with including a polychotomous categorical variable, recoded as multiple dummy variables (each mutually exclusive), in multiple imputation? I am using the Markov chain Monte Carlo method in SAS proc MI, and am concerned about internally inconsistent coding of missing values using this approach (and how to deal with these observations after MI, and before the analysis). For example, we have a variable coding point of maximum impact on the exterior of a vehicle involved in a motor vehicle crash. There are 4 categories within the variable (frontal, right-lateral, left-lateral, rear). I'd like to recode the variable as 3 dummy variables, each with rear collision as the reference, in order to include the variable in MI. Each of these 3 dummy variables would be mutually exclusive. That is, there can only be one point of maximum impact per vehicle. I'm not sure what to do with those observations imputed with a "1" for 2 or more of these dummy variables (e.g. both frontal and right-lateral impacts) in MI, nor do I know how much of a problem this may be. Any suggestions or similar experience? Any thoughts are welcome. Thanks.
Craig Craig D. Newgard, MD, MPH Research Fellow Department of Emergency Medicine Harbor-UCLA Medical Center 1000 West Carson Street, Box 21 Torrance, CA 90509 (310)222-3666 (Office) (310)782-1763 (Fax) [email protected]
