## steady state in WinNonlin (example) [Software]

Hi Antigoni,

❝ […] I discovered a defect in the calculation of univariate confidence intervals using WNL. I have already contacted Certara, who recognised the issue and shall proceed to relevant update. So, I would not recommend using the linear model 502 for confirmation of steady-state achievement for the time being.

Interesting. How did you discovered that? Using my example data in R:

t <- c(24, 48, 72, 96, 120) c <- c(18.71, 22.24, 22.44, 25.63, 23.25) m <- lm(c[3:5] ~ t[3:5]) # use only the last 3 summary(m) Call: lm(formula = c[3:5] ~ t[3:5]) Residuals:       1       2       3 -0.9283  1.8567 -0.9283 Coefficients:             Estimate Std. Error t value Pr(>|t|) (Intercept) 22.15333    6.56431   3.375    0.183 t[3:5]       0.01687    0.06700   0.252    0.843 Residual standard error: 2.274 on 1 degrees of freedom Multiple R-squared:  0.05966,   Adjusted R-squared:  -0.8807 F-statistic: 0.06344 on 1 and 1 DF,  p-value: 0.8429 anova(m) Analysis of Variance Table Response: c[3:5]           Df Sum Sq Mean Sq F value Pr(>F) t[3:5]     1 0.3280  0.3280  0.0634 0.8429 Residuals  1 5.1708  5.1708 confint(m, level=0.95)[2, ]      2.5 %     97.5 % -0.8343986  0.8681486

In Phoenix/WinNonlin 8.0:

Linear Model 502
Estimate        0.016875 StdError        0.066996687 UnivarCI_Lower -1.0886159 UnivarCI_Upper  1.1223659

Linear Mixed Effects
 Estimate    0.016875 StdError    0.066996687 Conf_Level 95 Lower_CI   -0.74019547 Upper_CI    0.77394547

Even in bloody M\$-Excel 2000 (!) I got an agreement with R up to the fifth significant digit:

 0.016875  0.066996687 -0.834394981  0.868144981

Dif-tor heh smusma 🖖🏼 Довге життя Україна!
Helmut Schütz

The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes