Bogus? What? [Software]
Dear ElMaestro,
Out of a walnut shell
you are right.
As long as you don't talk about a test of sequence effects.
The RANDOM statement produces the correct test automatically.
See above in this thread to notice that this is of relevance for a number of users (also with other software
), which are not so happy as you.
And as long as you don't talk about the educational benefit of specifying which of your effects you consider fixed or random, which opens you the way to mixed models software necessary for the evaluation of more complicated study designs.
I must confess that I never understand this SASophylistic "... post hoc fashion ...".
But what is actually done in Proc GLM is nowadays known as "method of moments" in the mixed model context.
BTW: Could you explain your "Linear model on Steroids" a bit more in detail? I couldn't get the the joke.
❝ The standard 2,2,2-BE model can be fit with a linear model or a mixed model (equivalently glm, lm, lme etc in R) and you can obtain the same results.
❝ When one uses the RANDOM statement in connection with PROC GLM, it means.......very little of relevance to the 2,2,2-B situation, as I see it.
❝ It can be omitted and we're still happy.
Out of a walnut shell

As long as you don't talk about a test of sequence effects.
The RANDOM statement produces the correct test automatically.
See above in this thread to notice that this is of relevance for a number of users (also with other software

And as long as you don't talk about the educational benefit of specifying which of your effects you consider fixed or random, which opens you the way to mixed models software necessary for the evaluation of more complicated study designs.
I must confess that I never understand this SASophylistic "... post hoc fashion ...".
But what is actually done in Proc GLM is nowadays known as "method of moments" in the mixed model context.
BTW: Could you explain your "Linear model on Steroids" a bit more in detail? I couldn't get the the joke.
—
Regards,
Detlew
Regards,
Detlew
Complete thread:
- SAS vs. WinNonlin: different sequence effect results Eva 2008-05-06 14:04 [Software]
- SAS vs. WinNonlin: different sequence effect results Ohlbe 2008-05-06 15:56
- imbalanced design? Helmut 2008-05-06 16:13
- Sample data & results Eva 2008-05-06 17:42
- Error factor Ohlbe 2008-05-06 19:25
- Error tests between/within Helmut 2008-05-06 21:33
- Error tests between/within Helmut 2008-05-07 18:18
- The power to know d_labes 2008-05-08 11:16
- The power to know Helmut 2008-05-08 17:18
- The power to know d_labes 2008-05-09 09:35
- The power to know Nirali 2008-05-09 11:00
- The power to know d_labes 2008-05-16 08:54
- The power to know Nirali 2008-05-09 11:00
- The power to know d_labes 2008-05-09 09:35
- The power to know kevan 2009-05-25 15:46
- Bogus statement for 2,2,2-BE ElMaestro 2009-05-25 22:25
- Bogus? What?d_labes 2009-05-27 08:57
- Linear model on steroids ElMaestro 2009-05-28 19:12
- Bogus? What?d_labes 2009-05-27 08:57
- Fixed nowadays what? d_labes 2009-05-27 09:03
- Bogus statement for 2,2,2-BE ElMaestro 2009-05-25 22:25
- The power to know Helmut 2008-05-08 17:18
- Kinetica 5.0 bug Helmut 2008-12-31 16:42
- Error tests between/within Helmut 2008-05-06 21:33
- Error factor Ohlbe 2008-05-06 19:25
- Sample data & results Eva 2008-05-06 17:42