[NMusers] Prediction with parameter estimates on new data

Hello NMusers, I am new to NONMEM, and I am unsure how to use parameter estimates for prediction with new data. More specifically, I have a K/PD nonlinear mixed effects model developed in NONMEM, and I want to check its predictive power in a specific way. The data I've been using has about 500 pat

RE: [NMusers] Prediction with parameter estimates on new data

Dear Lib, If you use the EVID data item (0 for observations 1 for doses) in your data set, you can denoted the observations for which you want to make a prediction by EVID=2 (other type event). That way they will not contribute to parameter estimation, but you will get predictions (both populat

Re: [NMusers] Prediction with parameter estimates on new data

That is good to know, but in this case I want to use everything for parameter estimation, and then get predictions using those parameter estimates on a subset of the data. Is there a way to use EVID data item for that? On Wed, Mar 19, 2014 at 10:29 AM, Mats Karlsson wrote: > Dear Lib, > > > >

RE: [NMusers] Prediction with parameter estimates on new data

Dear Lib, I don't think I fully understand what you are going for - do you want to use the final parameter estimates from your model, in tandem with early timepoint data from individuals to predict the later effects for that specific individual? If that is the case you could simply change the E

[NMusers] criteria for implementing BSV-V2 and BSV-Q

Dear all, In the present project a two compartmental structural model adequately describes our data. Estimated parameters are Cl, V1, Q and V2, between-subject varibility is estimated for CL and V1 - estimates are precise. In the further development of the structural model introduction of BSV o

[NMusers] RE: criteria for implementing BSV-V2 and BSV-Q

Dear Carolien, What type of sampling/how many subjects do you have data for? I think there are three main ways of handling your issue - first you can remove the the BSV on V2 and or Q (you may only try it on one). The second is to use the resulting model but to keep in mind that you are dealin

Re: [NMusers] criteria for implementing BSV-V2 and BSV-Q

Dear Carolien, Compare predictions (PRED and IPRED) between the models without and with BSV on the parameters of the second compartment. It could be that extra ETA accomodates few outlying points. 17 points of OF is not much (unless your data set is small). You may be better off with a stable