If you start with counts, the first example in the documentation SAS/STAT(R) 13.1 User's Guide shows how to incorporate them. As far as missing, how you address it depends on how it occurred. MCAR can generally be ignored, the missing data can be assumed to have equal impact on all groups. In those cases, your effective sample size is the non-missing observations. If the reason for the missing is known (MNAR), then you can incorporate that as a separate category in any statistical test. Alternately, for both MAR and MNAR, you can use PROC MCMC to actually model the process. The MCMC documentation has a good discussion of missingness ( SAS/STAT(R) 13.1 User's Guide ),
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