From: Ethan Wu <*ethan.wu75*>

Date: Fri, 28 May 2010 13:26:20 -0700 (PDT)

Hi Mat and all, if I understand correctly with my limted stat k=

nowledge, I guess it is fair to say NONMEM dose not explicitly assume no=

rmal distribution for Eta, but it is approximate (or assymptotical) to a =

normal distribution during the actual estimating. This is wh=

y when we simulate, it is OK to use the Eta estimate and assume it is n=

ormal distributed to draw the random subjects. ________=

________________________ From: Matt Hutmacher <matt.hutmacher

s] distribution assumption of Eta in NONMEM Hi Ethan, If th=

e random effects (etas) enter the model in a nonlinear way, then (consideri=

ng NONMEM VI or lower) one would consider an approximation to the overall l=

ikelihood which was based on assuming the random effects were normally dist=

ributed (Laplace approximation). If however, the random effects enter th=

e model in an additive way, no approximation is necessary. In this case,=

assumptions about the random effects are not as critical for estimation.=

The extended least squares estimates of the fixed effects and variance =

components of the model are consistent and asymptotically normal provided t=

he marginal variance (based on the random effects and epsilons) are correct=

ly specified. This property holds even if the data are not normally dist=

ributed. If the data are normal, then extended least squares is essen=

tially maximum likelihood and you get an efficiency to your estimates. (=

my statements are based on Chapter 9 of Linear and Nonlinear Models for

the Analysis of Repeated Measurements by Vonesh and Chinchilli) Be=

st, Matt From:owner-nmusers

globomaxnm.com] On Behalf Of Ethan Wu Sent: Friday, May 28, 2010 2:27 PM=

tion assumption of Eta in NONMEM I could not find in the NONMEM hel=

p guide that explicitly mentioned a normal distribution is assumed, only it=

was clearly mentioned of assumption of mean of zero. __________=

______________________ From:Serge Guzy <GUZY

<ethan.wu75

25:24 PM Subject: RE: [NMusers] distribution assumption of Eta in NONMEM=

ion programs like NONMEM, SADAPT, PDX-MC-PEM and SAEM. Therefore when you s=

imulate, random values from a normal distribution are generated. However, y=

ou have the flexibility to use any transformation to create distributions f=

or your model parameters that will depart from pure normality. For example,=

CL=theta(1)*exp(eta(1)) will generate a log-normal distribution for t=

he clearance although the random deviates are all from the normal distribut=

ion. I am not sure how you can simulate data sets if you are using the n=

on parametric option that is indeed available in NONMEM. Serge Guzy; Ph.D=

rom:owner-nmusers

ehalf Of Ethan Wu Sent: Friday, May 28, 2010 9:08 AM To: nmusers

axnm.com Subject: [NMusers] distribution assumption of Eta in NONMEM =

Dear users, Is it true NONMEM dose not assume Eta a normal di=

stribution? If it does not, I wonder what distribution it assumes? =

I guess this is critical when we do simulations. Thanks =

________________________________ The information contained in=

this email message may contain confidential or legally privileged informat=

ion and is intended solely for the use of the named recipient(s). No confid=

entiality or privilege is waived or lost by any transmission error. If the =

reader of this message is not the intended recipient, please immediately de=

lete the e-mail and all copies of it from your system, destroy any hard cop=

ies of it and notify the sender either by telephone or return e-mail. Any d=

irect or indirect use, disclosure, distribution, printing, or copying of an=

y part of this message is prohibited. Any views expressed in this message a=

re those of the individual sender, except where the message states otherwis=

e and the sender is authorized to state them to be the views of XOMA. =

Received on Fri May 28 2010 - 16:26:20 EDT

Date: Fri, 28 May 2010 13:26:20 -0700 (PDT)

Hi Mat and all, if I understand correctly with my limted stat k=

nowledge, I guess it is fair to say NONMEM dose not explicitly assume no=

rmal distribution for Eta, but it is approximate (or assymptotical) to a =

normal distribution during the actual estimating. This is wh=

y when we simulate, it is OK to use the Eta estimate and assume it is n=

ormal distributed to draw the random subjects. ________=

________________________ From: Matt Hutmacher <matt.hutmacher

s] distribution assumption of Eta in NONMEM Hi Ethan, If th=

e random effects (etas) enter the model in a nonlinear way, then (consideri=

ng NONMEM VI or lower) one would consider an approximation to the overall l=

ikelihood which was based on assuming the random effects were normally dist=

ributed (Laplace approximation). If however, the random effects enter th=

e model in an additive way, no approximation is necessary. In this case,=

assumptions about the random effects are not as critical for estimation.=

The extended least squares estimates of the fixed effects and variance =

components of the model are consistent and asymptotically normal provided t=

he marginal variance (based on the random effects and epsilons) are correct=

ly specified. This property holds even if the data are not normally dist=

ributed. If the data are normal, then extended least squares is essen=

tially maximum likelihood and you get an efficiency to your estimates. (=

my statements are based on Chapter 9 of Linear and Nonlinear Models for

the Analysis of Repeated Measurements by Vonesh and Chinchilli) Be=

st, Matt From:owner-nmusers

globomaxnm.com] On Behalf Of Ethan Wu Sent: Friday, May 28, 2010 2:27 PM=

tion assumption of Eta in NONMEM I could not find in the NONMEM hel=

p guide that explicitly mentioned a normal distribution is assumed, only it=

was clearly mentioned of assumption of mean of zero. __________=

______________________ From:Serge Guzy <GUZY

<ethan.wu75

25:24 PM Subject: RE: [NMusers] distribution assumption of Eta in NONMEM=

ion programs like NONMEM, SADAPT, PDX-MC-PEM and SAEM. Therefore when you s=

imulate, random values from a normal distribution are generated. However, y=

ou have the flexibility to use any transformation to create distributions f=

or your model parameters that will depart from pure normality. For example,=

CL=theta(1)*exp(eta(1)) will generate a log-normal distribution for t=

he clearance although the random deviates are all from the normal distribut=

ion. I am not sure how you can simulate data sets if you are using the n=

on parametric option that is indeed available in NONMEM. Serge Guzy; Ph.D=

rom:owner-nmusers

ehalf Of Ethan Wu Sent: Friday, May 28, 2010 9:08 AM To: nmusers

axnm.com Subject: [NMusers] distribution assumption of Eta in NONMEM =

Dear users, Is it true NONMEM dose not assume Eta a normal di=

stribution? If it does not, I wonder what distribution it assumes? =

I guess this is critical when we do simulations. Thanks =

________________________________ The information contained in=

this email message may contain confidential or legally privileged informat=

ion and is intended solely for the use of the named recipient(s). No confid=

entiality or privilege is waived or lost by any transmission error. If the =

reader of this message is not the intended recipient, please immediately de=

lete the e-mail and all copies of it from your system, destroy any hard cop=

ies of it and notify the sender either by telephone or return e-mail. Any d=

irect or indirect use, disclosure, distribution, printing, or copying of an=

y part of this message is prohibited. Any views expressed in this message a=

re those of the individual sender, except where the message states otherwis=

e and the sender is authorized to state them to be the views of XOMA. =

Received on Fri May 28 2010 - 16:26:20 EDT