RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread E.Olofsen
erred option, but one could also consider to bootstrap residuals. Jeroen From: e.olof...@lumc.nl [mailto:e.olof...@lumc.nl] Sent: Monday, March 31, 2014 13:08 To: Elassaiss - Schaap, J (Jeroen); gej1...@cam.ac.uk; nmusers@globomaxnm.com Subject: RE: [NMusers] NONMEM vs SPSS Hi Jeroen, The BOOT

RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread Elassaiss - Schaap, J (Jeroen)
, but one could also consider to bootstrap residuals. Jeroen From: e.olof...@lumc.nl [mailto:e.olof...@lumc.nl] Sent: Monday, March 31, 2014 13:08 To: Elassaiss - Schaap, J (Jeroen); gej1...@cam.ac.uk; nmusers@globomaxnm.com Subject: RE: [NMusers] NONMEM vs SPSS Hi Jeroen, The BOOTSTRAP option

RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread E.Olofsen
- Schaap, J (Jeroen) [jeroen.elassaiss-sch...@merck.com] Sent: Monday, March 31, 2014 12:23 PM To: Gavin Jarvis; nmusers@globomaxnm.com Subject: RE: [NMusers] NONMEM vs SPSS Dear Gavin, Reading back your original post, if your data are really N=1 and you have this perfect fit phenomenon there is

RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread Elassaiss - Schaap, J (Jeroen)
approaches use all sampling over subjects. (There are other ways of doing a bootstrap) From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of Gavin Jarvis Sent: Monday, March 31, 2014 11:33 To: nmusers@globomaxnm.com Subject: RE: [NMusers] NONMEM vs SPSS Dear All

RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread Gavin Jarvis
m.com Subject: RE: [NMusers] 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 re

RE: [NMusers] NONMEM vs SPSS

2014-03-31 Thread Elassaiss - Schaap, J (Jeroen)
; 'Gavin Jarvis'; nmusers@globomaxnm.com Subject: RE: [NMusers] 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

RE: [NMusers] NONMEM vs SPSS

2014-03-29 Thread Bauer, Robert
to:robert.ba...@iconplc.com> Web: www.iconplc.com<http://www.iconplc.com/> From: owner-nmus...@globomaxnm.com [mailto:owner-nmus...@globomaxnm.com] On Behalf Of Ken Kowalski Sent: Saturday, March 29, 2014 3:44 PM To: 'Gavin Jarvis'; nmusers@globomaxnm.com Subject: RE: [NMusers] NO

RE: [NMusers] NONMEM vs SPSS

2014-03-29 Thread Ken Kowalski
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 s

Re: [NMusers] NONMEM vs SPSS

2014-03-29 Thread Nick Holford
Gavin, NONMEM has been noted (Senn et al 2012) to produce smaller SE (R-1 S R-1 method) compared to estimates from Mathcad, SAS, GenStat and R. The Mathcad estimates were identical to SAS, Genstat and R when using numerical derivatives and larger when based on the expected Fisher information

RE: [NMusers] NONMEM vs SPSS

2014-03-29 Thread E.Olofsen
Dear Gavin, Perhaps an idea is to compare the different MATRIX options of the covariance step of NONMEM, and with the bootstrap, to assess their relative properties. Erik From: owner-nmus...@globomaxnm.com [owner-nmus...@globomaxnm.com] on behalf of Gavin Jarvis