RE: NONMEM vs SPSS
I concur with Ken's statement, and I also prefer to use MATRIX=R as the first
choice for covariance assessment. On occasion, MATRIX=S can be used if there
are numerical difficulties in assessing the R matrix, and if there are enough
subjects relative to the dimension size (number of total parameters estimated)
of the variance-covariance matrix to be estimated.
Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics, R&D
ICON Development Solutions
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Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Ken Kowalski
Sent: Saturday, March 29, 2014 3:44 PM
To: 'Gavin Jarvis'; [email protected]
Subject: RE: [NMusers] NONMEM vs SPSS
Dear Gavin,
This is most likely because most nonlinear regression programs invert the
Hessian (second derivative matrix of the model with respect to the parameters)
to obtain the covariance matrix. This corresponds to the R matrix in NONMEM.
However, the default method that NONMEM uses is a sandwich estimator involving
both the Hessian (R) and the square of the first derivatives matrix (S). I
suspect that if you use the MATRIX=R option on the $COV step you will find that
the standard errors will now be in agreement with SPSS (NLR). I know Stu Beal
made the sandwich estimator the default as it is supposed to be more robust to
non-normality but I would have preferred the MATRIX=R option to be the default
to be more consistent with other nonlinear regression software implementations.
Ken
From: [email protected]<mailto:[email protected]>
[mailto:[email protected]] On Behalf Of Gavin Jarvis
Sent: Saturday, March 29, 2014 12:55 PM
To: [email protected]<mailto:[email protected]>
Subject: [NMusers] NONMEM vs SPSS
Dear NONMEM Users
Does anyone have a view on the relative merits/reliability/accuracy of NONMEM
($COV step) vs SPSS (NLR) with respect to their derived values of the parameter
standard errors and parameter correlation matrices?
The data I am analysing are single subject (not population). Parameter
estimates from the two programs are, to all intents and purposes, identical.
However, the SE values from NONMEM $COV are consistently smaller by
1.5-2.0-fold.
Any thoughts?
Gavin
__________________________________________________
Dr Gavin E Jarvis MA PhD VetMB MRCVS
University Lecturer in Veterinary Anatomy
Department of Physiology, Development & Neuroscience
Physiological Laboratory
Downing Street
Cambridge
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Fellow and College Lecturer in Pharmacology
Selwyn College
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