Transl Clin Pharmacol.  2016 Dec;24(4):161-168. 10.12793/tcp.2016.24.4.161.

R-based reproduction of the estimation process hidden behind NONMEM® Part 2: First-order conditional estimation

• Bae KS
• Yim DS

• KMID: 2413837
• DOI: http://doi.org/10.12793/tcp.2016.24.4.161

Abstract

The first-order conditional estimation (FOCE) method is more complex than the first-order (FO) approximation method because it estimates the empirical Bayes estimate (EBE) for each iteration. By contrast, it is a further approximation of the Laplacian (LAPL) method, which uses second-order expansion terms. FOCE without INTERACTION can only be used for an additive error model, while FOCE with INTERACTION (FOCEI) can be used for any error model. The formula for FOCE without INTERACTION can be derived directly from the extension of the FO method, while the FOCE with INTERACTION method is a slight simplification of the LAPL method. Detailed formulas and R scripts are presented here for the reproduction of objective function values by NONMEM.

Keyword

R NONMEM FOCE

MeSH Terms

Bays
Methods
Reproduction*

Figure

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  Figure 1. NONMEM control file for FOCE without INTERACTION

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  Figure 2. R script for FOCE without INTERACTION

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  Figure 3. NONMEM control file for FOCE with INTERACTION method

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  Figure 4. R script for FOCE with INTERACTION method

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  Figure 5. Comparison of WRES vs time plot in the proportional error model

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