Table 3.

Regression coefficients and model fit for different distribution models.

	Poisson regression	Negative binomial regression	Zero-inflated Poisson	Zero-inflated negative binomial	Hurdle Poisson	Hurdle negative binomial
Intercept	−1.17	−1.18	0.13	−1.01	0.16	−0.04
Std. error	0.35	0.54	0.39	0.50	0.40	0.59
p value	<0.001	0.03	0.7	0.046	0.7	0.9
Symptom days	0.092	0.104	0.069	0.107	0.067	0.077
Std. Error	0.007	0.014	0.009	0.014	0.009	0.015
p value	<0.001	<0.001	<0.001	0.017	<0.001	<0.001
Impulsivity	−.012	−.014	−0.015	−0.017	−0.015	−0.019
Std. Error	0.004	0.007	0.004	0.006	0.005	0.007
p value	0.006	0.053	<0.001	0.009	<0.001	0.004
AIC	514	458	467	454	467	459

Notes: Estimates are omitted for the zero-inflated and hurdle step of the model for simplicity. These are included in the tutorial files.