### Mediator model

Call:
lm(formula = bili ~ trt, data = data)

Residuals:
    Min      1Q  Median      3Q     Max 
-3.4000 -2.5000 -1.7000  0.4434 24.3000 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)  
(Intercept)   2.2132     0.8784   2.520   0.0123 *
trt           0.7434     0.5532   1.344   0.1801  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 4.594 on 274 degrees of freedom
Multiple R-squared:  0.006548,	Adjusted R-squared:  0.002923 
F-statistic: 1.806 on 1 and 274 DF,  p-value: 0.1801

### Outcome model

Call:
survival::survreg(formula = Surv(time, status) ~ trt + bili, 
    data = data, dist = "exponential")
              Value Std. Error      z      p
(Intercept)  8.4293     0.2768  30.45 <2e-16
trt          0.2217     0.1797   1.23   0.22
bili        -0.1220     0.0122 -10.02 <2e-16

Scale fixed at 1 

Exponential distribution
Loglik(model)= -1174.9   Loglik(intercept only)= -1206.3
	Chisq= 62.73 on 2 degrees of freedom, p= 2.4e-14 
Number of Newton-Raphson Iterations: 5 
n= 276 

### Mediation analysis 
            est        se          Z         p      lower      upper exp(est)
cde   0.2660128 0.2155844  1.2339151 0.2172345 -0.1565248 0.68855042 1.304752
pnde  0.2660128 0.2155844  1.2339151 0.2172345 -0.1565248 0.68855042 1.304752
tnie -0.1088633 0.0817301 -1.3319855 0.1828650 -0.2690513 0.05132474 0.896853
tnde  0.2660128 0.2155844  1.2339151 0.2172345 -0.1565248 0.68855042 1.304752
pnie -0.1088633 0.0817301 -1.3319855 0.1828650 -0.2690513 0.05132474 0.896853
te    0.1571495 0.2285489  0.6875968 0.4917067 -0.2907982 0.60509720 1.170171
pm   -0.7908608 1.4014647 -0.5643102 0.5725431 -3.5376812 1.95595957       NA
     exp(lower) exp(upper)
cde   0.8551103   1.990828
pnde  0.8551103   1.990828
tnie  0.7641040   1.052665
tnde  0.8551103   1.990828
pnie  0.7641040   1.052665
te    0.7476666   1.831430
pm           NA         NA

Evaluated at:
avar: trt
 a1 (intervened value of avar) = 2.3
 a0 (reference value of avar)  = 1.1
mvar: bili
 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.