1. How would QRPEM handle BQL? ...
M3 method is about handling BQL data during LL calculation for given parameters of some subject, So both Laplacian and QRPEM are applicable (the model is not Gaussian in such case)
2. Would it be possible to run step wise covariate search for categorical covariates?
yes, it is possible. in built-in mode enable(N) statement is added automatically for each covariate fixed effect irrespective of the covariate type.
step 0 is no covariate scenario, in other steps the covariate effects are added sequentially
thanks Simon for your reply
If I may follow up on couple of points pertaining to the second question please
- When I am trying to map the categorical covariates using QRPEM engine, If I added +1 for those, the model won't run, while if I chose yes instead, it would run fine. Any reason why? or how shall I address such issue?
- for the continuous covariates, for some reason, unlike Laplacian, QRPEM is not allowing me to have different values of the continuous covariates for each patient. So, for example, If I am trying to add creatinine as a covariate, and I had different measurements on different days, the model won't run. It will only run if I had those values set to same number (like baseline creatinine and have this number copied over for all cells). How can I address such issue?
Appreciate your help and support
Best,