RE: Fitting Data Below the Quantification Limit

From: Lewis B. Sheiner Date: January 10, 2004 technical Source: cognigencorp.com
From: Lewis B. Sheiner - lbs@lewisbsheiner.net Subject: RE: [NMusers] Fitting Data Below the Quantification Limit Date: 1/10/2004 5:21 PM All - As I understand it, NM6 should have built-in code to do the necessary integrations in a conveneint way. In the mean-time, here (below and attached) is some code that Russ Wada, Bill Poland, and I came up with that works at least on a very simple test problem. That's all the testing I've done. The code assumes Y|eta is normally distributed with expected value = MN and standard deviation = SD, so it will not work for time-to-event Y, logisticY, etc. LBS. ========================================================== $ERROR [or $PRED] MN= ... ; Your model for E(DV); often just F SD= ... ; Your model for SD(DV) QL= ... ; The QL -- A fixed value X=(QL-MN)/SD ABSX=X IF (X.LT.0) ABSX=-X ; compute -2LL contrib l2pi=1.837877 ; log 2*pi IF (DV .GT. QL) THEN ; >QL case: L=N(MN,SD2) Y = l2pi + 2*LOG(SD)+((DV-MN)/SD)**2 ENDIF IF (DV .LE. QL) THEN; >QL case: L=N(MN,SD2), need CUM NL ; Compute NN = Std CUM NL (STDNCDF) at X -- from Abramovitz & Stegun, ; Handbook of Mathematical Functions b1=0.31938153 b2=-0.356563782 b3=1.781477937 b4=-1.821255978 b5=1.330274429 pp=0.2316419 c2=0.3989423 tt=1/(1+ABSX*pp) b=c2*EXP(-1/2*ABSX**2) n1=((((b5*tt+b4)*tt+b3)*tt+b2)*tt+b1)*tt n2=1-b*n1 ENDIF IF(DV .LE. QL.AND.X.LT.0) THEN ; belongs in above 'IF' but can't nest NN=1-n2 ELSE NN = n2 ENDIF IF (DV.LT.QL.AND.ABSX.LT.6) THEN Y = -2*LOG(NN) ENDIF IF(DV .LE. QL .AND. X .GE. 6.0) THEN ; X > +6SD, STDNCDF~ 1 Y = 0 ENDIF IF(DV .LE. QL .AND. X .LE. -6.0) THEN ; X < -6SD, trunc to -2*log(1-STDNCDF(6)) Y = -37.8379 ; ENDIF $EST METHOD=COND LAPLACE -2LL $THETA ... $OMEGA ... ==================================================================== _______________________________________________________
Jan 06, 2004 Matt Hutmacher Fitting Data Below the Quantification Limit
Jan 10, 2004 Lewis B. Sheiner RE: Fitting Data Below the Quantification Limit