PHX build 6.3.0.395 / 6.4.0.511 [Software]
Hi Yung-jin,
There are small differences to bear, since I started from the raw data and performed NCA first. This is a complete, balanced data set; therefore, the same results for
Table
This table is missing for the fixed effects model in the current release 6.3 (build 6.3.0.395) – therefore my workaround, but available in pre-release 1.4 (build 6.4.0.511).
Of course in the mixed model for AUCt and AUCinf:
Table
Table
Note the CVintra is not reported (why not?)…
❝ […] Could you present the results (part of it will be good enough) from running PHX (or its beta)?
There are small differences to bear, since I started from the raw data and performed NCA first. This is a complete, balanced data set; therefore, the same results for
subject(sequence) random or fixed are expected.Table
Partial SSDependent Hypothesis DF SS MS F_stat P_value
Ln(Cmax) Sequence 1 0.0006903 0.0006903 0.02920 0.8672
Ln(Cmax) Sequence*Subject 12 0.2836764 0.0236397 1.32782 0.3155
Ln(Cmax) Formulation 1 0.0181691 0.0181691 1.02054 0.3323
Ln(Cmax) Period 1 0.0362379 0.0362379 2.03545 0.1792
Ln(Cmax) Error 12 0.2136406 0.0178034
Ln(AUCt) Sequence 1 0.0151077 0.0151077 0.71554 0.4142
Ln(AUCt) Sequence*Subject 12 0.2533637 0.0211136 0.63428 0.7791
Ln(AUCt) Formulation 1 0.0108554 0.0108554 0.32611 0.5785
Ln(AUCt) Period 1 0.0368259 0.0368259 1.10629 0.3136
Ln(AUCt) Error 12 0.3994534 0.0332878
Ln(AUCinf) Sequence 1 0.0143291 0.0143291 0.76043 0.4003
Ln(AUCinf) Sequence*Subject 12 0.2261202 0.0188434 0.60445 0.8022
Ln(AUCinf) Formulation 1 0.0150303 0.0150303 0.48214 0.5007
Ln(AUCinf) Period 1 0.0346915 0.0346915 1.11282 0.3122
Ln(AUCinf) Error 12 0.3740929 0.0311744This table is missing for the fixed effects model in the current release 6.3 (build 6.3.0.395) – therefore my workaround, but available in pre-release 1.4 (build 6.4.0.511).
Of course in the mixed model for AUCt and AUCinf:
Warning 11094: Negative final variance component. Consider omitting this VC structure.
Table
Final Variance parameters (mixed)Dependent Parameter Estimate
Ln(Cmax) Var(Sequence*Subject) 0.0029182
Ln(Cmax) Var(Residual) 0.0178034
Ln(Cmax) Intersubject CV 0.0540594
Ln(Cmax) Intrasubject CV 0.1340254
Ln(AUCt) Var(Sequence*Subject) -0.0060871
Ln(AUCt) Var(Residual) 0.0332878
Ln(AUCt) Intrasubject CV 0.1839783
Ln(AUCinf) Var(Sequence*Subject) -0.0061655
Ln(AUCinf) Var(Residual) 0.0311744
Ln(AUCinf) Intrasubject CV 0.1779478Table
Final Variance parameters (fixed)Dependent Parameter Estimate
Ln(Cmax) Var(Residual) 0.0178034
Ln(AUCt) Var(Residual) 0.0332878
Ln(AUCinf) Var(Residual) 0.0311744Note the CVintra is not reported (why not?)…
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Dif-tor heh smusma 🖖🏼 Довге життя Україна!![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
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The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Dif-tor heh smusma 🖖🏼 Довге життя Україна!
![[image]](https://static.bebac.at/pics/Blue_and_yellow_ribbon_UA.png)
Helmut Schütz
![[image]](https://static.bebac.at/img/CC by.png)
The quality of responses received is directly proportional to the quality of the question asked. 🚮
Science Quotes
Complete thread:
- How to calculate intersubject variability in PHX WinNonlin zan 2014-01-29 23:58 [Software]
- Negative variance component Helmut 2014-01-30 01:16
- Negative variance component zan 2014-01-30 18:11
- Negative variance component zan 2014-01-31 00:16
- Negative variance component ElMaestro 2014-01-31 08:20
- Negative variance component yjlee168 2014-01-31 10:26
- Example data set Helmut 2014-02-01 16:03
- Example data set yjlee168 2014-02-01 17:40
- PHX build 6.3.0.395 / 6.4.0.511Helmut 2014-02-02 02:04
- PHX build 6.3.0.395 / 6.4.0.511 yjlee168 2014-02-02 07:54
- PHX build 6.3.0.395 / 6.4.0.511Helmut 2014-02-02 02:04
- Example data set yjlee168 2014-02-01 17:40
- Example data set Helmut 2014-02-01 16:03
- Negative variance component ElMaestro 2014-02-01 16:31
- Negative variance component yjlee168 2014-02-01 17:47
- Just thinking loud ElMaestro 2014-02-01 19:02
- All models are wrong… Helmut 2014-02-02 02:31
- another book for linear model yjlee168 2014-02-02 08:07
- All models are wrong… Helmut 2014-02-02 02:31
- Just thinking loud ElMaestro 2014-02-01 19:02
- References Helmut 2014-02-02 02:19
- References ElMaestro 2014-02-02 09:56
- Negative variance component yjlee168 2014-02-01 17:47
- Negative variance component – Chow/Liu d_labes 2014-02-03 09:02
- Negative variance component – Chow/Liu ElMaestro 2014-02-03 10:22
- Variance components – Proc mixed d_labes 2014-02-03 11:58
- Variance components – Proc mixed ElMaestro 2014-02-03 12:58
- Variance components – Proc mixed 90% CIs d_labes 2014-02-03 13:16
- Variance components – Proc mixed Helmut 2014-02-03 14:14
- FDA code for non-replicate crossover? d_labes 2014-02-03 15:54
- Proc GLM rulez Helmut 2014-02-03 16:16
- Variance components – Proc mixed yjlee168 2014-02-03 20:43
- NOBOUND Helmut 2014-02-03 22:08
- FDA code for non-replicate crossover? d_labes 2014-02-03 15:54
- Variance components – Proc mixed ElMaestro 2014-02-03 12:58
- Variance components – Proc mixed d_labes 2014-02-03 11:58
- lm() or lme() for 2x2x2 study design? yjlee168 2014-02-03 20:22
- lm() or lme() for 2x2x2 study design? ElMaestro 2014-02-03 22:11
- lm() or lme() for 2x2x2 study design? yjlee168 2014-02-04 13:09
- bear for 2x2x2 study with negative variance components yjlee168 2014-02-05 19:12
- lm() or lme() for 2x2x2 study design? yjlee168 2014-02-04 13:09
- lm() or lme() for 2x2x2 study design? ElMaestro 2014-02-03 22:11
- Negative variance component – Chow/Liu ElMaestro 2014-02-03 10:22
- Negative variance component Helmut 2014-01-30 01:16
