Table 1.

Simulation statistics of the estimated natural indirect effect for a continuous exposure and a dichotomous outcome, n = 200.

Scenario	True Y Model	True M Model	Risk Difference, IE(x)RD (%)						Odds Ratio, log(IE(x)OR)
			True IE	Ave Est IE	Ave PE (%)	SD of Est IE	AVE SE	CP (%)	True log(IE)	Ave Est log(IE)	Ave PE (%)	SD of Est log(IE)	AVE SE	CP (%)
Binary Mediator
1	Logit	Logit	1.07	1.09	1.7	0.67	0.66	91.1	0.068	0.069	2.1	0.041	0.040	91.1
2	Logit	Probit	0.81	0.84	4.4	0.61	0.59	92.7	0.051	0.053	3.8	0.037	0.036	92.8
3	Probit	Logit	0.74	0.78	5.2	0.57	0.56	91.1	0.047	0.049	4.6	0.035	0.035	91.9
4	Probit	Probit	0.82	0.86	5.8	0.60	0.60	93.6	0.052	0.054	4.1	0.036	0.037	93.6
Continuous Mediator
5	Logit	Lin†	0.85	0.83	−2.0	0.50	0.51	91.5	0.046	0.046	−1.0	0.027	0.028	92.6
6	Logit	Mix†	0.71	0.64	−9.1	0.53	0.52	92.5	0.038	0.034	−8.8	0.028	0.027	92.9
7	Probit	Lin†	0.88	0.92	5.6	0.57	0.54	93.0	0.049	0.052	5.9	0.031	0.030	93.3
8	Probit	Mix†	0.87	0.81	−7.4	0.64	0.64	93.1	0.042	0.039	−7.4	0.030	0.030	93.7

^†Lin, a linear regression model for the continuous mediator M with normally distributed residuals; Mix, a Gaussian mixture model for the continuous mediator M with a weighted sum of two Gaussian component densities.