### Mediator model

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

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.0072  -0.9198  -0.6511   1.1623   1.8965  

Coefficients:
            Estimate Std. Error z value Pr(>|z|)    
(Intercept) -1.09095    1.02743  -1.062 0.288315    
trt         -0.22689    0.32051  -0.708 0.479009    
age         -0.02366    0.01586  -1.492 0.135744    
male         1.77461    0.47253   3.756 0.000173 ***
stage        0.66646    0.19644   3.393 0.000692 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 264.30  on 195  degrees of freedom
Residual deviance: 234.79  on 191  degrees of freedom
AIC: 244.79

Number of Fisher Scoring iterations: 4

### Outcome model

Call:
glm(formula = spiders ~ trt + bili_bin + age + male + stage, 
    family = poisson(link = "log"), data = data)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.2406  -0.6409  -0.4672   0.3725   1.7315  

Coefficients:
             Estimate Std. Error z value   Pr(>|z|)    
(Intercept) -3.141587   0.665612  -4.720 0.00000236 ***
trt         -0.122282   0.174156  -0.702    0.48259    
bili_bin     0.706257   0.215332   3.280    0.00104 ** 
age         -0.004515   0.009071  -0.498    0.61870    
male        -1.119239   0.456004  -2.454    0.01411 *  
stage        0.607282   0.138548   4.383 0.00001170 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for poisson family taken to be 1)

    Null deviance: 198.14  on 275  degrees of freedom
Residual deviance: 161.34  on 270  degrees of freedom
AIC: 333.34

Number of Fisher Scoring iterations: 5

### Mediation analysis 
             est         se          Z         p      lower      upper  exp(est) exp(lower) exp(upper)
cde  -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
tnie -0.04083804 0.06029779 -0.6772725 0.4982330 -0.1590195 0.07734346 0.9599846  0.8529797   1.080413
tnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnie -0.04083804 0.06029779 -0.6772725 0.4982330 -0.1590195 0.07734346 0.9599846  0.8529797   1.080413
te   -0.18757662 0.21766927 -0.8617506 0.3888248 -0.6142005 0.23904730 0.8289656  0.5410733   1.270039
pm    0.20203003 0.33913391  0.5957235 0.5513600 -0.4626602 0.86672028        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: age male stage
 c_cond (covariate vector value) = 50 1 2

Note that effect estimates do not vary over m_cde and c_cond values when interaction = FALSE.

### Re-evaluation at c_cond = cmean
             est         se          Z         p      lower      upper  exp(est) exp(lower) exp(upper)
cde  -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
tnie -0.04747044 0.06830213 -0.6950067 0.4870511 -0.1813402 0.08639928 0.9536387  0.8341516   1.090242
tnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnie -0.04747044 0.06830213 -0.6950067 0.4870511 -0.1813402 0.08639928 0.9536387  0.8341516   1.090242
te   -0.19420903 0.22007417 -0.8824708 0.3775223 -0.6255465 0.23712842 0.8234858  0.5349690   1.267604
pm    0.22680281 0.36384334  0.6233529 0.5330526 -0.4863170 0.93992265        NA         NA         NA
