Variance components – Proc mixed [Software]
Haha, thanks Detlefffff,
This is mindblowing. I can't say that I understand in any way, but it is clear that the unbounded (=unfiddled, native and pure) optimisation analysis results in the same residual as the all-fixed lm/anova.
The million-dollar question asked in the nastiest fashion:
Do you either
believe in negative variances between subjects
-or-
would you inflate the MSE and get wide confidence intervals?




An agonising choice indeed.
Another wrong question: Why care about between-Vars in a 2,2,2-BE? Why not just do the anova, fetch the residual, calculate a CI on basis of it and punch any guy who asks about betweens hard in the face?
I wonder how the PK-workgroup at EMA would deal with this.
I can't say I understand any details of the stats but this thread opened my eyes to an issue that I had no idea existed. Thanks.

❝ Variance parameters are by default in SAS restricted to ≥0 in the maximization of the likelihood.
❝ Reasonable to me .
❝ I get negative variance for subject(sequence) in case of ln(AUCt) only if I use the non-standard NOBOUND option in the Proc MIXED call:
❝ ln(AUCt)
❝ V(subject(sequence))= -0.00609
❝ V(residual) = 0.03329
❝ Seems the same as PHX build 6.3.0.395 / 6.4.0.511 results. See Helmut's post above.
This is mindblowing. I can't say that I understand in any way, but it is clear that the unbounded (=unfiddled, native and pure) optimisation analysis results in the same residual as the all-fixed lm/anova.
The million-dollar question asked in the nastiest fashion:
Do you either
believe in negative variances between subjects
-or-
would you inflate the MSE and get wide confidence intervals?




An agonising choice indeed.
Another wrong question: Why care about between-Vars in a 2,2,2-BE? Why not just do the anova, fetch the residual, calculate a CI on basis of it and punch any guy who asks about betweens hard in the face?
I wonder how the PK-workgroup at EMA would deal with this.
I can't say I understand any details of the stats but this thread opened my eyes to an issue that I had no idea existed. Thanks.

—
Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
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 / 6.4.0.511 Helmut 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 / 6.4.0.511 Helmut 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 mixedElMaestro 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 mixedElMaestro 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