### 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 = "weibull")
               Value Std. Error     z       p
(Intercept)   8.8862     0.4204 21.14 < 2e-16
trt           0.0166     0.2601  0.06  0.9491
bili_bin     -1.3617     0.4825 -2.82  0.0048
trt:bili_bin  0.0612     0.3015  0.20  0.8392
Log(scale)   -0.2922     0.0736 -3.97 7.2e-05

Scale= 0.747 

Weibull distribution
Loglik(model)= -1162.4   Loglik(intercept only)= -1203.8
	Chisq= 82.81 on 3 degrees of freedom, p= 7.7e-18 
Number of Newton-Raphson Iterations: 5 
n= 276 

### Mediation analysis 
            est         se         Z         p      lower     upper exp(est)
cde  0.12273038 0.28511557 0.4304584 0.6668623 -0.4360859 0.6815466 1.130580
pnde 0.03606078 0.24621957 0.1464578 0.8835600 -0.4465207 0.5186423 1.036719
tnie 0.02753849 0.07712466 0.3570646 0.7210434 -0.1236231 0.1787001 1.027921
tnde 0.03480150 0.25104669 0.1386256 0.8897460 -0.4572410 0.5268440 1.035414
pnie 0.02879777 0.08053238 0.3575924 0.7206483 -0.1290428 0.1866383 1.029216
te   0.06359927 0.26137036 0.2433301 0.8077497 -0.4486772 0.5758758 1.065665
pm   0.44081770 1.76515889 0.2497326 0.8027942 -3.0188302 3.9004656       NA
     exp(lower) exp(upper)
cde   0.6465622   1.976933
pnde  0.6398505   1.679745
tnie  0.8837129   1.195662
tnde  0.6330278   1.693579
pnie  0.8789364   1.205191
te    0.6384721   1.778688
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.