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From: Dennis Fisher <fisher_at_plessthan.com>

Date: Wed, 28 Feb 2018 10:43:46 -0800

Leonid

With your assistance, I realized the difference between the NONMEM and R =

approaches — the R approach allows only between-period =

differences in intercept (not slope) whereas the NONMEM approach that I =

implemented allowed for between-period differences in both. I removed =

the ETA for slope from the NONMEM code — the NONMEM results =

matches R exactly.

Conceptually, a common slope makes sense for this particular analysis.

Problem solved — thanks for your thoughts.

Dennis

Dennis Fisher MD

P < (The "P Less Than" Company)

Phone / Fax: 1-866-PLessThan (1-866-753-7784)

www.PLessThan.com <http://www.plessthan.com/>

*> On Feb 28, 2018, at 9:59 AM, Leonid Gibiansky =
*

<lgibiansky_at_quantpharm.com> wrote:

*>
*

*> see "Random slopes" here:
*

*>
*

*> =
*

https://web.stanford.edu/class/psych252/section/Mixed_models_tutorial.html=

*>
*

*> lmer(pitch ~condition+gender+(1 + condition | subject))
*

*>
*

*>
*

*>
*

*> On 2/28/2018 12:27 PM, Dennis Fisher wrote:
*

*>> Leonid
*

*>> I omitted one critical piece of information:
*

*>> $INPUT PERIOD=ID
*

*>> I think that your approach implies an order to the data from =
*

different periods — whereas making PERIOD=ID allows NONMEM to =

see each treatment as a separate subject (i.e., the random effect)

*>> Dennis
*

*>> Dennis Fisher MD
*

*>> P < (The "P Less Than" Company)
*

*>> Phone / Fax: 1-866-PLessThan (1-866-753-7784)
*

*>> www.PLessThan.com <http://www.plessthan.com/>
*

*>>> On Feb 28, 2018, at 9:23 AM, Leonid Gibiansky =
*

<lgibiansky_at_quantpharm.com <mailto:lgibiansky_at_quantpharm.com>> wrote:

*>>>
*

*>>> Just checking: you have treatment effect in R but no effect in =
*

Nonmem, am I correct? (I have not used R nlme for a long time, may be I =

am interpreting it incorrectly)

*>>>
*

*>>> Should you code nonmem as
*

*>>> $PRED
*

*>>> INTERCEPT= THETA(1) + THETA(3)*PERIOD + ETA(1)
*

*>>> SLOPE= THETA(2) + THETA(4)*PERIOD + ETA(2)
*

*>>> Y= INTERCEPT + SLOPE * TIME + EPS(1)
*

*>>>
*

*>>> Leonid
*

*>>>
*

*>>> On 2/28/2018 11:16 AM, Dennis Fisher wrote:
*

*>>>> Colleagues
*

*>>>> I am implementing a linear mixed-effects model in R.
*

*>>>> Out of curiosity (and to confirm that I was doing the right thing), =
*

I wrote the code initially in NONMEM, then tried to replicate the =

results in R.

*>>>> The dataset is four (identical) treatments for one subject and the =
*

data are reasonably linear.

*>>>> For most subjects, the results from the NONMEM analysis are nearly =
*

identical to those from R.

*>>>> But, for one subject, the SLOPE/INTERCEPT are sufficiently =
*

different to concern me that I am implementing one of these (or possibly =

both) incorrectly.

*>>>> The critical code is:
*

*>>>> *NONMEM:*
*

*>>>> $PREDINTERCEPT= THETA(1) + ETA(1)
*

*>>>> SLOPE= THETA(2) + ETA(2)
*

*>>>> Y= INTERCEPT + SLOPE * TIME + EPS(1)
*

*>>>> *R: LMER package:*
*

*>>>> lmer(DV ~ TIME + (1|PERIOD), data=DATA, REML=FALSE)
*

*>>>> where:
*

*>>>> DV is the dependent variable
*

*>>>> PERIOD distinguishes the treatments (and is a factor)
*

*>>>> *R: NLME package:*
*

*>>>> lme(DV ~ TIME, random = ~ 1|PERIOD, data=DATA, method="ML")
*

*>>>> The two R packages yield identical results.
*

*>>>> Graphics from NONMEM and R differ slightly but there is no obvious =
*

preference between these approaches.

*>>>> Any thoughts as to a possible explanation?
*

*>>>> Dennis
*

*>>>> Dennis Fisher MD
*

*>>>> P < (The "P Less Than" Company)
*

*>>>> Phone / Fax: 1-866-PLessThan (1-866-753-7784)
*

*>>>> www.PLessThan.com =
*

<http://www.plessthan.com/><http://www.plessthan.com/>

Received on Wed Feb 28 2018 - 13:43:46 EST

Date: Wed, 28 Feb 2018 10:43:46 -0800

Leonid

With your assistance, I realized the difference between the NONMEM and R =

approaches — the R approach allows only between-period =

differences in intercept (not slope) whereas the NONMEM approach that I =

implemented allowed for between-period differences in both. I removed =

the ETA for slope from the NONMEM code — the NONMEM results =

matches R exactly.

Conceptually, a common slope makes sense for this particular analysis.

Problem solved — thanks for your thoughts.

Dennis

Dennis Fisher MD

P < (The "P Less Than" Company)

Phone / Fax: 1-866-PLessThan (1-866-753-7784)

www.PLessThan.com <http://www.plessthan.com/>

<lgibiansky_at_quantpharm.com> wrote:

https://web.stanford.edu/class/psych252/section/Mixed_models_tutorial.html=

different periods — whereas making PERIOD=ID allows NONMEM to =

see each treatment as a separate subject (i.e., the random effect)

<lgibiansky_at_quantpharm.com <mailto:lgibiansky_at_quantpharm.com>> wrote:

Nonmem, am I correct? (I have not used R nlme for a long time, may be I =

am interpreting it incorrectly)

I wrote the code initially in NONMEM, then tried to replicate the =

results in R.

data are reasonably linear.

identical to those from R.

different to concern me that I am implementing one of these (or possibly =

both) incorrectly.

preference between these approaches.

<http://www.plessthan.com/><http://www.plessthan.com/>

Received on Wed Feb 28 2018 - 13:43:46 EST