[R-meta] Meta-analysis with small number of effects: 3 options

Hello R meta Community,

I'm meta-analyzing 55 effects from 27 longitudinal studies. However, there are only 3 studies that collectively offer 4 post-test2 effects.

Given the unreliable nature of post-test2 results, I'm considering 3 options:

1- Include these 4 effects in analyses but exclude them from interpretation (and/or data display).

2- Exclude these 4 effects from data and of course analyses altogether.

3- Merge post-test1 and post-test2 categories into one category (called post-test) but then methodologically adjust for the fact that the 3 studies with post-test2 effects likely took longer to complete than other studies.

Which one seems more reasonable? (results below)

#Option1: Removing 4 delayed effects from data display but not data:
 time Mean SE Df Lower Upper t p-value Sig.
1 baseline -0.191 0.159 18.000 -0.526 0.144 -1.200 0.246
2 posttest1 0.719 0.126 18.000 0.455 0.982 5.723 0.000 ***
3 posttest2 0.384 0.323 18.000 -0.295 1.063 1.187 0.250

#Option2:  Removing 4 delayed effects altogether from data:
 time Mean SE Df Lower Upper t p-value Sig.
1 baseline -0.182 0.163 19.000 -0.523 0.160 -1.115 0.279
2 posttest1 0.722 0.127 19.000 0.456 0.987 5.681 0.000 ***

#Option3: After merge:
 time Mean SE Df Lower Upper t p-value Sig.
1 baseline -0.178 0.157 19.000 -0.507 0.151 -1.132 0.272
2 posttest 0.690 0.120 19.000 0.438 0.942 5.735 0.000 ***

Thanks so much and I look forward to hearing from you.

Best wishes,

Zhouhan