### 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 = "weibull")
               Value Std. Error      z      p
(Intercept)  8.26928    0.19748  41.87 <2e-16
trt          0.15845    0.12738   1.24   0.21
bili        -0.10040    0.00934 -10.75 <2e-16
Log(scale)  -0.34643    0.07511  -4.61  4e-06

Scale= 0.707 

Weibull distribution
Loglik(model)= -1165.7   Loglik(intercept only)= -1203.8
	Chisq= 76.03 on 2 degrees of freedom, p= 3.1e-17 
Number of Newton-Raphson Iterations: 6 
n= 276 

### Mediation analysis 
             est        se          Z         p      lower      upper  exp(est)
cde   0.19014456 0.1528561  1.2439446 0.2135200 -0.1094480 0.48973708 1.2094244
pnde  0.19014456 0.1528561  1.2439446 0.2135200 -0.1094480 0.48973708 1.2094244
tnie -0.08956246 0.0671626 -1.3335168 0.1823623 -0.2211987 0.04207382 0.9143312
tnde  0.19014456 0.1528561  1.2439446 0.2135200 -0.1094480 0.48973708 1.2094244
pnie -0.08956246 0.0671626 -1.3335168 0.1823623 -0.2211987 0.04207382 0.9143312
te    0.10058210 0.1653583  0.6082676 0.5430100 -0.2235142 0.42467843 1.1058144
pm   -0.97916699 1.9566679 -0.5004258 0.6167753 -4.8141656 2.85583157        NA
     exp(lower) exp(upper)
cde   0.8963288   1.631887
pnde  0.8963288   1.631887
tnie  0.8015574   1.042971
tnde  0.8963288   1.631887
pnie  0.8015574   1.042971
te    0.7997035   1.529099
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.