Dear Meta-Analysis Colleagues,
We are meta-analyzing 73 longitudinal studies. But we have doubts
amongst us regarding how to combine the longitudinal effects of these
studies.
On the one hand, if we use time only as an indicator of testing
occasions (pre-test and post-tests), and then use it as fixed and
random-effect as in:
rma.mv(es ~ time_id, random = ~ time_id | study, struct = "UN")
then, we have longitudinally combined apples and oranges. That is,
time 1 in one study may have covered six months, but time 1 in another
study may have covered 6 days. This, we think, is problematic in terms
of the interpretation of both the fixed and random-effects of time.
So, we have coded for both time_id (testing occasions indicator) and
time_meaning_wks (length of actual time up to each testing occasion in
weeks).
We are wondering how we should incorporate time_meaning_wks into our model?
Any help is appreciated,
Stefanou
study time_id time_meaning_wks
1 0 0
1 1 4
1 2 6
2 0 0
2 1 1