### Mediator model

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

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 + 
    trt:bili_bin, data = data, dist = "exponential")
               Value Std. Error     z      p
(Intercept)   9.2078     0.5557 16.57 <2e-16
trt           0.0274     0.3483  0.08 0.9374
bili_bin     -1.6564     0.6408 -2.59 0.0097
trt:bili_bin  0.0437     0.4038  0.11 0.9138

Scale fixed at 1 

Exponential distribution
Loglik(model)= -1169.3   Loglik(intercept only)= -1206.3
	Chisq= 74.05 on 3 degrees of freedom, p= 5.8e-16 
Number of Newton-Raphson Iterations: 5 
n= 276 

### Mediation analysis 
            est         se         Z         p      lower     upper exp(est)
cde  0.10629627 0.38178196 0.2784214 0.7806889 -0.6419826 0.8545752 1.112151
pnde 0.04173257 0.34924907 0.1194923 0.9048853 -0.6427830 0.7262482 1.042616
tnie 0.03285015 0.09188457 0.3575154 0.7207060 -0.1472403 0.2129406 1.033396
tnde 0.04099885 0.35469634 0.1155886 0.9079786 -0.6541932 0.7361909 1.041851
pnie 0.03358388 0.09383305 0.3579110 0.7204099 -0.1503255 0.2174933 1.034154
te   0.07458273 0.36475046 0.2044760 0.8379815 -0.6403150 0.7894805 1.077434
pm   0.44965572 2.11928459 0.2121734 0.8319718 -3.7040658 4.6033772       NA
     exp(lower) exp(upper)
cde   0.5262480   2.350376
pnde  0.5258270   2.067310
tnie  0.8630866   1.237311
tnde  0.5198613   2.087967
pnie  0.8604278   1.242957
te    0.5271263   2.202252
pm           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 can vary over m_cde and c_cond values when interaction = TRUE.