Bag full of bugs [Study Performance]
I’m too lazy to check with my old installation of Kinetica. But there are some points to note:
❝ SOURCE D.F SS MS F p
❝ Period 1 0.0264787 0.0264787 0.56186 0.4669 NS
❝ Subject(Seq) 13 4.8517 0.373208 7.91934 0.0003379 ***
❝ Formulation 1 0.211625 0.211625 4.4906 0.05391 NS
❝ Sequence 1 0.686301 0.686301 14.5631 0.002141 ***
❝ Error 13 0.61264 0.0471261
❝ Total 29 6.38875
Old story. Kinetica calculates the sequence effect wrong – since ages. See this thread.
Instead of F=0.686301/0.0471261=14.5631 (which is highly significant with p=0.002141) the correct test is against
Subject(Seq)
: F=0.686301/0.373208=1.8389 (which is not significant with p=0.1982).❝ Root Mean Square Error = 0.217086
The RMSE is a crude estimate of the CV and should be avoided.
❝ ; CV = 0.0347883
That’s nonsense!
\(CV\% = 100\sqrt{e^{0.0471261}-1} = 21.97\%\)
❝ Power of the test = 0.500777
❝ 1 - ( Power of the test ) = 0.499223
Wrong. If you insist in post hoc power: 0.09885. With a T/R-ratio close to the upper limit of the acceptance range would you really expect a ~50% chance to pass BE in 15 subjects?
❝ around the ratio:[test form]/[ref form])=[1.028, 1.3612]
Yes, but around which ratio? I would guess: \(\sqrt{1.028 \times 1.3612} = {\color{Red} {1.829\ldots}}\) The geometric mean of Test is 559.01 and the one of Reference 461.21. As a first guess of the T/R-ratio we get 461.21/559.01=1.2121. Since this is an imbalanced dataset, we have to use the least squares (or adjusted) means instead, which are 552.58 and 456.58. Therefore, T/R=1.2103. What does Kinetica “calculate” here?
![[image]](img/uploaded/image4.gif)
Hypothesis DF SS MS F_stat P_value
Period 1 0.027982 0.027982 0.07021 0.79519
Sequence*Patient 13 5.181510 0.398578 7.49434 0.00045
Sequence 1 0.105223 0.105223 1.97847 0.18300
Formulation 1 0.271883 0.271883 5.11214 0.04155
Error 13 0.691389 0.053184
T/R 121.02% [90% CI: 104.22%, 140.53%]
BTW:
Parameter Estimate
Var(Sequence*Patient) 0.172697
Var(Residual) 0.053184
Intersubject CV 0.434173
Intrasubject CV 0.233717
Check: \(CV\% = 100\sqrt{e^{0.053184}-1} = 23.37\%\).
![[image]](img/uploaded/image28.png)
If you want an independent evaluation by noncommercial software: In
121.02% [104.22–140.53%] CV 23.37%
![[image]](img/uploaded/image28.png)
❝ I havnt randomisation of subject 15, and then they put the result in kinetica they excluded him,
The randomization of an excluded subject is not required anyhow.
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:
- randomization khaoula 2014-06-06 14:04
- Imbalanced cross-overs Helmut 2014-06-06 14:47
- Imbalanced cross-overs khaoula 2014-06-06 16:03
- CV 0.03%? Helmut 2014-06-07 13:52
- Imbalanced cross-overs jag009 2014-06-09 15:36
- Imbalanced cross-overs khaoula 2014-06-09 22:07
- Bag full of bugsHelmut 2014-06-10 00:37
- Randomisation? ElMaestro 2014-06-10 01:00
- Randomisation? Helmut 2014-06-10 14:53
- Randomisation? khaoula 2014-06-11 00:17
- Problems resolved? Helmut 2014-06-11 02:01
- Problems resolved? khaoula 2014-07-24 13:36
- corrected data in PHX/WNL Helmut 2014-07-27 01:37
- Problems resolved? khaoula 2014-07-24 13:36
- Problems resolved? Helmut 2014-06-11 02:01
- Randomisation? khaoula 2014-06-11 00:17
- Randomisation? Helmut 2014-06-10 14:53
- Randomisation? ElMaestro 2014-06-10 01:00
- Which version of Kinetica? Helmut 2014-06-11 19:51
- Which version of Kinetica? khaoula 2014-06-12 00:41
- Which version of Kinetica? khaoula 2014-07-25 00:49
- adjusted means (aka LSMs) Helmut 2014-07-27 02:23
- adjusted means (aka LSMs) khaoula 2014-08-25 21:41
- adjusted means (aka LSMs) Helmut 2014-07-27 02:23
- Bag full of bugsHelmut 2014-06-10 00:37
- Imbalanced cross-overs khaoula 2014-06-09 22:07
- Imbalanced cross-overs khaoula 2014-06-06 16:03
- Imbalanced cross-overs Helmut 2014-06-06 14:47