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

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept) -1.55900    0.47386  -3.290    0.001 ** 
trt         -0.01657    0.27560  -0.060    0.952    
bili_bin     1.23969    0.28418   4.362 1.29e-05 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 332.32  on 275  degrees of freedom
Residual deviance: 311.86  on 273  degrees of freedom
AIC: 317.86

Number of Fisher Scoring iterations: 4

### Mediation analysis 
             est         se           Z         p      lower     upper
cde  -0.01988166 0.33071517 -0.06011718 0.9520623 -0.6680715 0.6283082
pnde -0.01988166 0.33071517 -0.06011718 0.9520623 -0.6680715 0.6283082
tnie -0.02880160 0.08138271 -0.35390312 0.7234115 -0.1883088 0.1307056
tnde -0.01988166 0.33071517 -0.06011718 0.9520623 -0.6680715 0.6283082
pnie -0.02880160 0.08138271 -0.35390312 0.7234115 -0.1883088 0.1307056
te   -0.04868326 0.34048521 -0.14298201 0.8863044 -0.7160220 0.6186555
pm    0.58572232 4.13301922  0.14171778 0.8873029 -7.5148465 8.6862911
      exp(est) exp(lower) exp(upper)
cde  0.9803147  0.5126964   1.874437
pnde 0.9803147  0.5126964   1.874437
tnie 0.9716092  0.8283589   1.139632
tnde 0.9803147  0.5126964   1.874437
pnie 0.9716092  0.8283589   1.139632
te   0.9524828  0.4886924   1.856430
pm          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.