### Mediator model

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

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-2.0116  -1.0649  -0.5783   1.0511   1.7122  

Coefficients:
            Estimate Std. Error z value   Pr(>|z|)    
(Intercept) -1.53024    0.85116  -1.798    0.07220 .  
trt         -0.17117    0.25982  -0.659    0.51003    
age         -0.01386    0.01299  -1.067    0.28610    
male         1.33046    0.43911   3.030    0.00245 ** 
stage        0.74640    0.16356   4.563 0.00000503 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 382.49  on 275  degrees of freedom
Residual deviance: 349.60  on 271  degrees of freedom
AIC: 359.6

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 -0.03231246 0.05067699 -0.6376160 0.5237237 -0.1316375 0.06701262 0.9682040  0.8766587   1.069309
tnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnie -0.03231246 0.05067699 -0.6376160 0.5237237 -0.1316375 0.06701262 0.9682040  0.8766587   1.069309
te   -0.17905105 0.21517220 -0.8321291 0.4053361 -0.6007808 0.24267871 0.8360632  0.5483833   1.274659
pm    0.16748203 0.30271996  0.5532573 0.5800872 -0.4258382 0.76080225        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 -0.03521846 0.05453535 -0.6457915 0.5184144 -0.1421058 0.07166886 0.9653945  0.8675295   1.074300
tnde -0.14673859 0.20898674 -0.7021430 0.4825900 -0.5563451 0.26286790 0.8635197  0.5733006   1.300655
pnie -0.03521846 0.05453535 -0.6457915 0.5184144 -0.1421058 0.07166886 0.9653945  0.8675295   1.074300
te   -0.18195705 0.21613422 -0.8418706 0.3998604 -0.6055723 0.24165824 0.8336371  0.5457620   1.273359
pm    0.17962266 0.31763092  0.5655075 0.5717287 -0.4429225 0.80216782        NA         NA         NA
