Proc GLM with missings for 2x2 crossover [Outliers]
Dear Helmut!
As others meanwhile have already guessed: From the observation that the 90% CIs for 2x2x2 crossover are the same, regardless of one period missing or removing the subject with that missing (see f.i. this post).
The subject with the missing does not contribute to the error variance (mse) and by coincidence the df are also equal. Example 24 subjects:
df(error)=N-2=21 if one subject removed
df(error)=N-2=22 if all subjects included, minus 1 for the missing =21.
❝ BTW, I wonder where the origin of this rumour might be.
As others meanwhile have already guessed: From the observation that the 90% CIs for 2x2x2 crossover are the same, regardless of one period missing or removing the subject with that missing (see f.i. this post).
The subject with the missing does not contribute to the error variance (mse) and by coincidence the df are also equal. Example 24 subjects:
df(error)=N-2=21 if one subject removed
df(error)=N-2=22 if all subjects included, minus 1 for the missing =21.
—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- "Removal" of an outlier: subject vs period lechia 2013-08-06 23:23
- "Removal" of an outlier: subject vs period ElMaestro 2013-08-07 11:09
- Canada: subject, not period Helmut 2013-08-07 13:48
- Proc GLM with missings d_labes 2013-08-07 14:46
- Proc GLM with missings jag009 2013-08-07 15:03
- Proc GLM with missings Helmut 2013-08-07 15:21
- Proc GLM with missings ElMaestro 2013-08-07 15:39
- Proc GLM with missings ElMaestro 2013-08-07 16:22
- Proc GLM random d_labes 2013-08-07 16:46
- Proc GLM with missings for 2x2 crossoverd_labes 2013-08-07 16:34
- Proc GLM with missings ElMaestro 2013-08-07 15:39
- Canada: subject, not period lechia 2013-08-07 15:46
- Canada: subject, not period Helmut 2013-08-07 15:57
- Canada: subject, not period lechia 2013-08-12 15:48
- Proc GLM with missings d_labes 2013-08-07 14:46