V [🇷 for BE/BA]
Dear d_labes,
Interesting. Let us discuss for a moment the covariance matrix V (not Z and not G, and at this point also not discussing which syntax SAS applies for the given problem (leaves disussions about CSH, FA(0) out here)).
V holds the key.
Further, let us assume for simplicity we only look at the first subject which is the first 4x4 of V where the data are ordered as TRTR (i.e. per1-per2-per3-per4 for the first subject; in the original dataset above they were ordered differently but the order in this context does not change the point):
Data in per1 and per3 correlate within the subject as (s)he gets T (within variance VT).
Data in per2 and per4 correlate within the subject as (s)he gets R (within variance VR).
To this we add a common error variance on the diagonal (V0).
Having no particular mathematical understanding, the first 4x4 of V I think will be:
Both of the models discussed above correspond to a fit with this V, as far as I can see.
❝ where are the intra-individual (error or residual) variances or sd for Test and Reference?
❝ You have only one residual.
❝ The trt1 and trt2 variances (and corr) in your output are the between subject covariance parameter.
Interesting. Let us discuss for a moment the covariance matrix V (not Z and not G, and at this point also not discussing which syntax SAS applies for the given problem (leaves disussions about CSH, FA(0) out here)).
V holds the key.
Further, let us assume for simplicity we only look at the first subject which is the first 4x4 of V where the data are ordered as TRTR (i.e. per1-per2-per3-per4 for the first subject; in the original dataset above they were ordered differently but the order in this context does not change the point):
Data in per1 and per3 correlate within the subject as (s)he gets T (within variance VT).
Data in per2 and per4 correlate within the subject as (s)he gets R (within variance VR).
To this we add a common error variance on the diagonal (V0).
Having no particular mathematical understanding, the first 4x4 of V I think will be:
V0+VT 0 VT 0
0 V0+VR 0 VR
VT 0 V0+VT 0
0 VR 0 V0+VR
Both of the models discussed above correspond to a fit with this V, as far as I can see.
—
Pass or fail!
ElMaestro
Pass or fail!
ElMaestro
Complete thread:
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- SAS? or R? or what? d_labes 2009-04-23 15:07
- FDA loves SAS code? definitely. yjlee168 2009-04-23 10:46
- FDA loves SAS code? d_labes 2009-04-23 09:48
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