Re: Mixture model for Disease Progression
Mahesh,
Do you have a good biological reason to divide your population into different subpopulations?
If not then a more flexible way to describe an association between baseline and slope is estimate the covariance between the random effects. This does carry with it the explicit assumption that the mixture model makes about the existence of different sub-populations.
Nick
Quoted reply history
On 15/01/2011 11:12 a.m., Samtani, Mahesh [PRDUS] wrote:
> Hello,
>
> I am trying some simple linear disease progression analysis and the data suggests that there are 2 populations in the dataset (Low Baseline, Low Slope vs. High Baseline, High Slope). It appears that that population consists of progressers and non-progressers (The Pharmacometrics textbook describes some code with 3 populations i.e. positive slope, zero slope, and negative slope but I want to keep my model simple).
>
> This is the only piece of the code that seems to work for my dataset. If I try to estimate THETA(3) in my code it causes the model to either becomes unstable or I get a very small negative value for THETA(3) with very poor precision. I would really appreciate feedback from NMusers on the parameterization of the slope parameter in this model (thetas and etas for the 2 populations).
>
> Many thanks in advance...MNS
>
> $PK
>
> CALLFL =1
>
> EST=MIXEST
>
> IF (MIXNUM.EQ.2) THEN
>
> BASE=THETA(2)*EXP(ETA(2))
>
> SLOP=THETA(4)+ETA(4)
>
> ELSE
>
> BASE=THETA(1)*EXP(ETA(1)) ; PATHOLOGIC BASELINE
>
> SLOP=THETA(3)*(1+ETA(3)) ; PATHOLOGIC PROGRESSION PARAMETER; ETA PARAMETERIZATION BASED ON TUTURIAL FROM PAGE
>
> ENDIF
>
> $THETA
>
> (0,15 ) ; BASELINE PATHOLOGIC
>
> (0,7) ; BASELINE NON-PATHOLOGIC
>
> (0,0.1) ; SLOPE PATHOLOGIC
>
> (0 FIX ) ; SLOPE NON-PATHOLOGIC
>
> $OMEGA BLOCK(1) 0.15
>
> $OMEGA BLOCK(1) SAME
>
> $OMEGA BLOCK(1) 0.35
>
> $OMEGA BLOCK(1) 0.03
--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology& Clinical Pharmacology
University of Auckland,85 Park Rd,Private Bag 92019,Auckland,New Zealand
tel:+64(9)923-6730 fax:+64(9)373-7090 mobile:+64(21)46 23 53
email: [email protected]
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford