Incorporating standard deviation (SD) on fitted mean values
Dear NONMEM users,
1) I am fitting Studies-reported means of a parameter X measured in human
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 mean of
parameter X at TIME=t, the "SD" is the standard deviation of the observations
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 between
STUDY variability on A
ALPHA = THETA(2)*EXP(ETA(2)) ;ETA2 is between STUDY
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 inform
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
included the SDs in anyway in the model fitting. I only accounted for the
number of subjects in the error model. I am not sure if there is a way to
account 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,
Ahmad Abuhelwa
Adelaide, South Australia
Australia
Email:
[email protected]<mailto:[email protected]>