Example 4 in SASophylistic [🇷 for BE/BA]

posted by d_labes  – Berlin, Germany, 2008-09-30 11:43 (6105 d 09:31 ago) – Posting: # 2441
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Dear folks,

if you need an independent opinion (no R, no Far side but 'the power to know' :-D) here are the results of log-linear regression with SAS for example 4 up to 6 decimals, without point Cmax, tmax:
N used lambdaZ     Rsq      Adj.Rsq
 3     0.119676  0.996846  0.993692
 4     0.126202  0.993931  0.990895
 5     0.128630  0.994243  0.992324
 6     0.127205  0.994425  0.993032

If I understood the algorithm right, 3 points in the terminal phase should be the solution.

From WinNONLIN users guide (dont know which version, found it on the Inder-net):
"[...] WinNonlin repeats regressions using the last three points with non-zero concentrations, then the last four points, last five, etc. Points prior to Cmax [...] are not used [...] For each regression, an adjusted R2 is computed [...] The regression with the largest adjusted R2 is selected to estimate lambdaZ, with these caveats:
  • If the adjusted R2 does not improve, but is within 0.0001 of the largest adjusted R2 value, the regression with the larger number of points is used.
  • lambdaZ must be positive, and calculated from at least three data points."

If you use Cmax, tmax one gets:
N used lambdaZ     Rsq      Adj.Rsq
 7     0.127446  0.995071  0.994086

If the algorithm is not serial (stop if no increase in adjR2), and this seems to be the case, then Nused=7;

Regards,

Detlew
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