Hello.  I am looking for help with a certain covariate for a logistic model.  This is a vaccine study where the endpoint is an event (0 or 1).  There are 3 doses administered.  We would like to somehow incorporate the effect of when the event occurs: between dose 1 and 2 (dose=1), between dose 2 and 3(dose=2), or after dose 3(dose=3).  Due to the design of the study we do not feel that using dose=1,2,3 as a continuous variable is appropriate.   Could it be treated as an ordinal variable?  Could be decomposed into indicator variables like Dose=dose1, dose2, dose3.   What is the best method to use in the model such that SAS applies the effect appropriately?  Currently we have model  event = treatment dose1 dose2 dose3 (and the interactions) where dose1, dose2, dose3 are categorical y/n=1/0, but the model fails due to low counts for dose1.  We tried combining dose1 and dose2 and still get this warning:  WARNING: There is possibly a quasi-complete separation of data points. The maximum likelihood estimate may not exist. WARNING: The LOGISTIC procedure continues in spite of the above warning. Results shown are based on the last maximum likelihood iteration. Validity of the model fit is questionable.   However, when I use the ordinal option, it runs fine.  But want to make sure it's valid.   Thank you for your time. ... View more