# [NMusers] Incorporating standard deviation (SD) on fitted mean values

Date: Sun, 15 Nov 2015 22:46:28 +0000

Dear NONMEM users,

1) I am fitting Studies-reported means of a parameter X measured in hu=
man subjects as a function of TIME. The studies report the mean plus/minus =
SD of that parameter rather than the actual subject measurements.

2) A snapshot of the main columns in my nmdata is provided below. The =
"ID" column represent the STUDY number, the "DV" column is the reported mea=
n of parameter X at TIME=t, the "SD" is the standard deviation of the obs=
ervations in the subjects at TIME=t.

3) I am using \$PRED for fitting.

4) I am using one exponential decline function to fit the means~TIME. =
I am weighting for the number of subjects in each study in the error model.

A = THETA(1)*EXP(ETA(1)) ;ETA1 is bet=
ween STUDY variability on A

ALPHA = THETA(2)*EXP(ETA(2)) ;ETA2 is between STU=
DY variability on ALPHA

IPRED = (A)*exp(-ALPHA*TIME)

Y = IPRED *(1+EPS(1)/SQRT(NSUB))

My Question:

5) Is there any way where I can incorporate the SDs that I have to inf=
orm about the between SUBJECT variability in the model fitting?

I am able to get a very good model as described above; however, I haven't i=
ncluded the SDs in anyway in the model fitting. I only accounted for the nu=
mber of subjects in the error model. I am not sure if there is a way to ac=
count for SDs either in the error model or if there is a way to incorporate=
them to the DVs?

I would appreciate any thoughts on this. Thank you.

ID

NSUB

TIME

DV

SD

1

10

0.083333

4.776667

0.230317

1

10

0.5

3.713333

0.355235

1

10

0.583333

3.556667

0.361091

1

10

0.75

3.2

0.339621

1

10

1.083333

2.816667

.

1

10

1.333333

2.613333

0.304487

1

10

1.416667

2.823333

0.290825

1

10

2

2.23

0.202992

2

5

0.5

6.36

0.329154

2

5

1

6

.

2

5

1.5

5.76

0.821635

2

5

2

5.18

0.973441

2

5

2.5

4.76

1.347797

2

5

3

4.13

1.680903

2

5

3.5

3.17

1.618905

Sincerely,