Dear Katya and Bill,
Thanks a lot for your suggestion. Multiple IGNORE, as suggested Katya,
actually worked.
Best Regards
On 18 November 2014 17:24, Ekaterina Gibiansky
wrote:
> Hi Xinting,
>
> You can separate the condition into several statements. For example, if
> you need to accept (A=1 O
Dear SoJeong,
First you might want to answer the question whether that phenotype is indeed
important in your dataset. With the initial popPK model you could plot posthoc
clearance against bodyweight and/or inspect the posthocs of clearance for
evidence of multiple peaks in your distribution. Yo
Dear SoJeong,
I agree with everything Jeroen proposed. In addition to that, you may want to
code the subjects with missing genotype as genotype 99 (or something similar)
and then estimate genotype as categorical covariate on CL. This approach is not
elegant but it is quick and often useful for
I would do mixture model only if there is a very large -several folds-
difference in PK parameters for two genotypes. If the difference is
comparable with the inter-subject variability within the genotype, I
would introduce category "missing" to remove the effect of those
subjects on covariate
Hi SoJeong,
I agree with Leonid here on the value of the mixture model. With potentially
subtle changes, mixture models can be very difficult. One way that I've had
luck previously with a similar approach is to make "unknown genotype" a
separate category and then to fit a parameter that is fr
Hi,
I would use:
IF (GENOTYPE.EQ.1) GENE = THETA(1)
IF (GENOTYPE.EQ.2) GENE = THETA(2)
IF (GENOTYPE.EQ.-99.AND.MIXNUM.EQ.1) GENE = THETA(1)
IF (GENOTYPE.EQ.-99.AND.MIXNUM.EQ.2) GENE = THETA(2)
$MIX
P(1)=THETA(3)
P(2)=1-P(1)
..
To handle THETA(3) there are different options
If I believe th
Hey Bill & SoJeong,
in your suggestion (Bill), you would estimate a fixed effect for the unknown
genotype weighting between G1 and G2.
But let's assume that the status "genotype unknown" is completely at random, so
some are of type 1 and some are of type 2.
Wouldn't it be possible to implement
Hello All Nonmem Users,
I am modeling intra-gastric H+ concentrations as PD biomarker, which
varies from 10e-7 to 10e-1. I log-transformed original data and used "Y =
LOG(IPRED)+EPS(1)" as log-linear error model firstly. The profile could be
simulated well, but when I fitted data, error messa
