1. Regarding "Did the interventions affect sickness days?"
1.1) Good.
1.2) So when it says the below it means that my model predicts that at wave 2 (post) the number of sickness days should be slightly higher?
Control#0: 1
Control#1: 1,02
1.2.1) The word "predict" confuses me. Does the coefficients express that there are actual difference between the two time periods?
All my coefficients is strongly significant (0,000), which is quite strange since the
command only give slightly significant results for only one of my treatment groups.
1.3) I thought you just said that is this command there is no space for controls?
1.4) I have 4.000 unique observations. When I run these commands it's down to 2000?
3. Regarding "whether perceptions of leadership style influence sick days (regardless of interventions)"
Super!
Although I'm pretty sure my employee_id and time DO identify my observations.
4. Reporting
I'm not sure how to report this in a paper. Would my table look like something below? (I wouldn't put p in parenthesis in the actual paper).

1.1) Good.
1.2) So when it says the below it means that my model predicts that at wave 2 (post) the number of sickness days should be slightly higher?
Control#0: 1
Control#1: 1,02
1.2.1) The word "predict" confuses me. Does the coefficients express that there are actual difference between the two time periods?
All my coefficients is strongly significant (0,000), which is quite strange since the
xtpoisson y i.treatment##i.time, fe
1.3) I thought you just said that is this command there is no space for controls?

1.4) I have 4.000 unique observations. When I run these commands it's down to 2000?
3. Regarding "whether perceptions of leadership style influence sick days (regardless of interventions)"
Super!
Although I'm pretty sure my employee_id and time DO identify my observations.
4. Reporting
I'm not sure how to report this in a paper. Would my table look like something below? (I wouldn't put p in parenthesis in the actual paper).
Comment