i have a measurement on patients at 3 fixed timepoints, but at each timepoint the 'treatment' can change between two types (this is not a 'designed' experiment such as incomplete blocks crossover that would randomise treatment sequence to patients, and it is not literally a 'treatment', it is just easier to explain it this way). Hypothetical data would appear as follows
patient timepoint treatment Y
1 1 a #
1 2 a #
1 3 b .
2 1 b #
2 2 a #
2 3 b #
3 1 a .
3 2 a #
3 3 a #
thus a patient does not necessary receive both 'treatments' (a and b), the data are messy eg unbalanced + missing data (Y=outcome). It seems to me patients should be included as random effects. Maybe it is analogous to a split plot design, with patients as a blocking factor, although i read that "with PROC GLM, you must use a TEST statement to obtain the correct F test for A" (https://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_mixed_sect0...). Thus is the following code insufficient?:
proc glm;
class patient timepoint treatment;
model y = patient timepoiint treatment treatment*timepoint / ss3;
random patient;
run;
although it is repeated measures, the repeated statement doesn't seem useful here because the 'treatment' changes over time.
Thanks for any advice
