Dear Tao, Cholesky decomposition is used to obtain the inverse square root of the covariance matrix in order to go from prediction discrepancies (pd) (1) to prediction distribution error (PDE). Normalized prediction distribution errors (NPDE) are obtained using the inverse function of the normal cumulative function (2). So if you have more than one observation per subject, it is better to compute NPDE.
To ways to compute easily NPDE: · use the R package an read the paper from Emmanuelle Comets(3) (the numerical results are saved in a file with extension .npde (the name of which is given by the user; the file contains the components id, xobs, ypred, npde) · NPDE are also available in NONMEM7 $TAB NPDE CWRES DV PRED RES WRES ESAMPLE=1000 SEED=1234567; number of simulation used to compute NPDE and the seed ONEHEADER NOAPPEND NOPRINT FILE=EXAMPLE.TAB Best regards, Karl (1) F. Mentré, S. Escolano, Prediction discrepancies for the evaluation of nonlinear mixed-effects models, J.Pharmacokinet. Biopharm. 33 (2006) 345–367. (2) K. Brendel, E. Comets, C. Laffont, C. Laveille, F. Mentré. Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide, Pharm. Res.23 (2006) 2036–2049. (3) E. Comets, K.Brendel, F. Mentré. Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models:The npde add-on package for R. De : [email protected] [mailto:[email protected]] De la part de Tao Liu Envoyé : vendredi 22 novembre 2013 03:55 À : [email protected] Objet : [NMusers] NPDE Calculation Dear Nmusers, I have two questions regarding to the calculation of NPDE and the corresponding package in R. 1) In Cholesky decompsition, should I calculate pd for each observation separately using corresponding mean and sd, or I should use the var-cov matrix and calculate pd for all the observations simultaneously? Should I consider the covariance between different observations here? 2) How can I save the individual NPDE value from the autonpde function in R ? Thanks, -- Tao Liu BSc PhD Student Center for Translational Medicine University of Maryland, Baltimore http://www.ctm.umaryland.edu/ Email: [email protected]<mailto:[email protected]> ＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝ The information in this email is confidential, and is intended solely for the addressee(s). Access to this email by anyone else is unauthorized and therefore prohibited. If you are not the intended recipient you are notified that disclosing, copying, distributing or taking any action in reliance on the contents of this information is strictly prohibited and may be unlawful. If you are not an addressee, please inform the sender immediately. Thanks a lot! ＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝＝
