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_sect033.htm). 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 ... View more