My data set consists of a survey of organizations across three waves to understand their delivery of services during covid. Its panel data is from three waves of the survey in the long format. Some organizations participated in all three waves of the survey (1-3), some just participated in 2 waves (wave 1&2 or 1&3), and most just participated in one survey. My current data is unbalanced. Please see the example of the dataset below.

clear
input
int ID int wave int delivery int budget int type int concern
1 1 1 1 1 3
1 2 3 1 1 4
1 3 4 1 1 5
2 1 2 3 2 3
3 1 4 2 1 4
3 3 5 2 1 5
5 1 3 1 2 3
5 2 4 1 2 5
10 1 3 3 3 3
10 2 4 3 3 4
10 3 5 3 3 5


xtset ID wave

Since my dependent variable (delivery) is ordinal and time-varying, I am using xtologit. I am interested in understanding the effect of time (wave 1-3) on my independent variable (concern). I tried to read Allison's book but I am not sure how to include time-varying IV in the model. That is, model organization's concern's across wave 1,2 & 3 and its effect on DV (delivery).
Thanks so much for the help!