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Figure 13.8.1 A Suitable Weighting Scheme for these Plasma Data may be Constant CV
As shown in Figure 13.8.1 a constant coefficient of variation (CV) for a series of data points translates into a weighting scheme described as the reciprocal of the observed value squared. Since there are two data sets fitted simultaneously it is important to scale the weight for each line appropriately. Thus, the b value of power is 2 and the a value is the square of the CV.
Figure 13.8.2 A Suitable Weighting Scheme for these Urine Data may be Constant SD
If these estimates of CV (for the plasma data) and SD (for the urine data) are reasonable then a good optimization should be possible with reasonable scatter in the weighted residual plots, Chapter 9.
** FINAL OUTPUT FROM Boomer (v3.0.8) ** 09-Feb-2003 --- 11:38:29 am Title: Fit to two lines simultaneously Input: From Ch1308.BAT Output: To Ch1308.OUT Data for [Drug] came from Ch1308p.DAT Data for Drug in Urine came from Ch1308u.DAT Fitting algorithm: DAMPING-GAUSS/SIMPLEX Weighting for [Drug] by 1/a*Cp(Obs )^b With a = 0.2500E-02 and b = 2.000 Weighting for Drug in Urine by 1/a*Cp(Obs )^b With a = 25.00 and b = 0.0000 Numerical integration method: 2) Fehlberg RKF45 with 2 de(s) With relative error 0.1000E-03 With absolute error 0.1000E-03 DT = 0.1000E-02 PC = 0.1000E-04 Loops = 2 Damping = 1 ** FINAL PARAMETER VALUES *** # Name Value S.D. C.V. % Lower <-Limit-> Upper 1) ke 0.14030 0.465E-03 0.33 0.00 10. 2) km 0.68668E-01 0.627E-03 0.91 0.00 10. 3) V 25.045 0.159 0.63 0.10 0.10E+03 AIC = -1.28240 Log likelihood = -12.3 Schwartz factor = -16.2293 Final WSS = 0.594419 R-squared = 1.000 Correlation Coeff = 1.000Try it out yourself with the Boomer .BAT and .DAT files (Macintosh (OS 9), Macintosh (OS X), and DOS versions as zip Archives
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