|
Distribution of productivity loss outcome
|
Number of Observations in each arm
|
Truncated negative binomial distributions of productivity loss outcomes in the two arms
|
Number of databases with quasi-complete separationa
|
|---|
|
80:15:5/60:30:10
|
100
|
Equal Scale
|
3
|
|
80:15:5/60:30:10
|
100
|
Unequal Scale
|
7
|
|
80:15:5/60:30:10
|
200
|
Equal Scale
|
0
|
|
80:15:5/60:30:10
|
200
|
Unequal Scale
|
0
|
|
60:35:5/40:50:10
|
100
|
Equal Scale
|
0
|
|
60:35:5/40:50:10
|
100
|
Unequal Scale
|
0
|
|
60:35:5/40:50:10
|
200
|
Equal Scale
|
0
|
|
60:35:5/40:50:10
|
200
|
Unequal Scale
|
0
|
|
50:40:10/30:55:15
|
50
|
Equal Scale
|
0
|
|
50:40:10/30:55:15
|
50
|
Unequal Scale
|
2
|
|
50:40:10/30:55:15
|
100
|
Equal Scale
|
0
|
|
50:40:10/30:55:15
|
100
|
Unequal Scale
|
0
|
|
50:40:10/30:55:15
|
200
|
Equal Scale
|
0
|
|
50:40:10/30:55:15
|
200
|
Unequal Scale
|
0
|
- aThe maximum likelihood estimate may not exist while running multinomial logistic regression for the three-part models. For number of observations = 50 and 5% max loss, a large number of databases with quasi-separation and thus the three-part model was not considered for these scenarios
