Hi all,

I am deciding between a school and year fixed effects model and an individual fixed effects model. I wonder which one makes the most sense.
My data have two waves. The outcome variable is continuous and the key predictor is a dummy. It is a nested dataset (individuals nested in schools). What are some of the statistical considerations for deciding which one to use?
One thing that comes to my mind is if there is enough variation in both my outcome and key independent variable across these two waves for an individual fixed effects model. I then did the following checks, but I am unsure what sufficient variable means for my case. I used multiple imputation to fill in the missing values of my predictor, and the imputed values follow the patterns of the observed values.

In addition, what are other things I should check to decide between these two models? Thank you so much!
Dependent variable:
RECODE of
dep_diff | Freq. Percent Cum.
--------------+-----------------------------------
No change. | 888 16.88 16.88
Change exists | 3,325 63.19 80.06
Missing value | 1,049 19.94 100.00
--------------+-----------------------------------
Total | 5,262 100.00


Independent variable:
RECODE of
predictor_
dff | Freq. Percent Cum.
--------------+-----------------------------------
No change | 2,727 51.82 51.82
Change exists | 1,485 28.22 80.05
Missing value | 1,050 19.95 100.00
--------------+-----------------------------------
Total | 5,262 100.00