# Estimation of standard error

From: Huali Wu <hualiw>
Date: Thu, 3 Jul 2008 13:28:23 -0400

Dear NMusers:

I am trying to fit a data set with concentrations of encapsulated drug =
and released drug. These concentrations were measured after an hour =
infusion of encapsulated drug. The problem is that I cannot get standard =
error estimated from simultaneous fitting of all the data. And I got an =
error message as below:

MINIMIZATION SUCCESSFUL
HOWEVER, PROBLEMS OCCURRED WITH THE MINIMIZATION.
REGARD THE RESULTS OF THE ESTIMATION STEP CAREFULLY, AND ACCEPT THEM =
ONLY
AFTER CHECKING THAT THE COVARIANCE STEP PRODUCES REASONABLE OUTPUT.
NO. OF FUNCTION EVALUATIONS USED: 968
NO. OF SIG. DIGITS IN FINAL EST.: 3.2
R MATRIX ALGORITHMICALLY NON-POSITIVE-SEMIDEFINITE
BUT NONSINGULAR
R MATRIX IS OUTPUT
COVARIANCE STEP ABORTED

But if I fit the encapsulated drug first and then fit data of both =
encapsulated drug and released drug by fixing the typical values of =
parameters associated with encapsulated drug compartment, I can get an =
estimation of standard errors. And GOF plots look good.

So my question is can I use this stepwise strategy to build up my base =
model? If not, what can I do to get standard error estimated in =
simultaneous fitting?

Any comment or suggestion will be highly appreciated.

Below is my code:

\$MODEL NPAR=8, NCOMP=3, COMP=(CENTRAL,DEFOBS),
COMP=(PERIPH1), COMP=(PERIPH2)

\$PK
V1 = THETA(1)*EXP(ETA(1))
V2 = THETA(2)*EXP(ETA(2))
V3 = THETA(3)
VM = THETA(4)
KM = THETA(5)
Q2 = THETA(6)*EXP(ETA(3))
Q3 = THETA(7)
Q4 = THETA(8)
S1 = V1
S2 = V1

\$ERROR

R1=0
IF (CMT.EQ.1) R1=1
R2=0
IF (CMT.EQ.2) R2=1
Y1=F+F*EPS(1)
Y2=F+F*EPS(1)
Y=R1*Y1+R2*Y2
IPRED=F
IRES=DV-IPRED

\$DES
C1 = A(1)/V1
DADT(2) = C1*VM/(KM+C1)+Q2*A(1)/V1 + Q4*A(3)/V3- =
Q3*A(2)/V2-Q4*A(2)/V2

\$THETA (5.27 FIX) (0, 0.5) (0, 3.38) (0.329 FIX) (4.38 FIX) (0.136 FIX) =
(0, 0.0626) (0, 0.0461)
\$OMEGA (0.01) (0.01) (0.01)
\$SIGMA (.1)

\$EST MAXEVAL=9999 PRINT=5
\$COV
\$TABLE ID TIME DV AMT RATE CMT NOPRINT FILE=ENCAP4 ONEHEADER
\$SCAT (RES WRES) VS TIME BY ID

Best regards,

Huali

Received on Thu Jul 03 2008 - 13:28:23 EDT

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