### Mediator model

Call:
glm(formula = bili_bin ~ trt, family = binomial(link = "logit"), 
    data = data)

Deviance Residuals: 
   Min      1Q  Median      3Q     Max  
-1.177  -1.141  -1.141   1.177   1.214  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)
(Intercept)  0.08577    0.38245   0.224    0.823
trt         -0.08577    0.24091  -0.356    0.722

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 382.49  on 275  degrees of freedom
Residual deviance: 382.36  on 274  degrees of freedom
AIC: 386.36

Number of Fisher Scoring iterations: 3

### Outcome model

Call:
survival::survreg(formula = Surv(time, status) ~ trt + bili_bin, 
    data = data, dist = "exponential")
              Value Std. Error     z       p
(Intercept)  9.1586     0.3175 28.85 < 2e-16
trt          0.0599     0.1762  0.34    0.73
bili_bin    -1.5907     0.2018 -7.88 3.3e-15

Scale fixed at 1 

Exponential distribution
Loglik(model)= -1169.3   Loglik(intercept only)= -1206.3
	Chisq= 74.04 on 2 degrees of freedom, p= 8.4e-17 
Number of Newton-Raphson Iterations: 5 
n= 276 

### Mediation analysis 
            est         se         Z         p      lower     upper exp(est) exp(lower) exp(upper)
cde  0.07188147 0.21141598 0.3400002 0.7338564 -0.3424862 0.4862492 1.074528  0.7100029   1.626205
pnde 0.07188147 0.21141598 0.3400002 0.7338564 -0.3424862 0.4862492 1.074528  0.7100029   1.626205
tnie 0.03334020 0.09313021 0.3579955 0.7203467 -0.1491917 0.2158721 1.033902  0.8614040   1.240944
tnde 0.07188147 0.21141598 0.3400002 0.7338564 -0.3424862 0.4862492 1.074528  0.7100029   1.626205
pnie 0.03334020 0.09313021 0.3579955 0.7203467 -0.1491917 0.2158721 1.033902  0.8614040   1.240944
te   0.10522167 0.23096318 0.4555777 0.6486937 -0.3474579 0.5579012 1.110957  0.7064818   1.747002
pm   0.32831570 0.03547485 9.2548855 0.0000000  0.2587863 0.3978451       NA         NA         NA

Evaluated at:
avar: trt
 a1 (intervened value of avar) = 2.3
 a0 (reference value of avar)  = 1.1
mvar: bili_bin
 m_cde (intervend value of mvar for cde) = 1.4
cvar: 
 c_cond (covariate vector value) = 

Note that effect estimates do not vary over m_cde and c_cond values when interaction = FALSE.
