lm() or lme() for 2x2x2 study design? [Software]
Hi Yung-jin,
EU: All fixed, no discussion.
US: All fixed, but lots of confusion because the SAS PROC GLM has the
Other places: Same, as far as I know. Some places might accept lme, but would probably at the outset nevertheless expect a simple linear model.
So
EU: All fixed, no discussion.
US: All fixed, but lots of confusion because the SAS PROC GLM has the
random
statement, giving users the impression that subject is treated as a random effect in the model.Other places: Same, as far as I know. Some places might accept lme, but would probably at the outset nevertheless expect a simple linear model.
So
lm
and not lme
for 2,2,2-BE.—
Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
Complete thread:
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- Example data set Helmut 2014-02-01 16:03
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- Negative variance component yjlee168 2014-02-01 17:47
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- 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
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- 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