I have a C Vs t data set with several points below the GC/MS LOQ. These points are critical, as they appear in the lambda Z portion of the curve.
Ahn, J et al J PKPD August 2008, and then subsequently Bergstand, M AAPS June 2009 recommend using a function in NONMEM called the F-Flag. For their M3 method, F-Flag is set to 0 (prediction) for samples above LOQ and set to 1 (a liklihood) for samples below LOQ.
How does one code the equivalent in Phoenix NLME, or is there a built in function similar to the M3 method?
1:Click on BQL in the interface in the error model
2: In the data set, put the LOQ value in the CObs column when you have BQL and create a censor column called for example CObs BQL and put 1 when it is BQL.
I’m investigating the item of Conc below the LLOQ for NLME modeling.
I have imported your example and understood the settings but not the output.
In your example two values were set to the likely LLOQ and thus flagged as censored in the CObsBQL column. M3 is supposed to estimate likelihood of this values and thus to provide an IPRED/PRED value necessarily below the LLOQ. Within outputs I don’t see any of this values. Just one line in residuals of the non-censored values. But the model accounts for likelihood of censored values I guess.
Sorry for my candidness. Which information can one expect from M3 use.
By the way, can M4 method be programmed in textual mode?