### 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 + trt:bili_bin + age + 
    male + stage, family = binomial(link = "logit"), data = data)

Deviance Residuals: 
    Min       1Q   Median       3Q      Max  
-1.4959  -0.7098  -0.4659   0.9611   2.3019  

Coefficients:
              Estimate Std. Error z value  Pr(>|z|)    
(Intercept)  -3.582569   1.180438  -3.035   0.00241 ** 
trt          -0.249105   0.470069  -0.530   0.59616    
bili_bin      1.011176   0.958044   1.055   0.29122    
age          -0.006281   0.014951  -0.420   0.67441    
male         -1.628478   0.588097  -2.769   0.00562 ** 
stage         0.917657   0.215085   4.266 0.0000199 ***
trt:bili_bin  0.058788   0.601373   0.098   0.92213    
---
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: 278.76  on 269  degrees of freedom
AIC: 292.76

Number of Fisher Scoring iterations: 5

### Mediation analysis 
             est         se          Z         p      lower     upper  exp(est) exp(lower) exp(upper)
cde  -0.20016298 0.67777364 -0.2953242 0.7677462 -1.5285749 1.1282489 0.8185973  0.2168445   3.090241
pnde -0.23932319 0.39943518 -0.5991540 0.5490702 -1.0222018 0.5435554 0.7871604  0.3598019   1.722119
tnie -0.06015561 0.09070684 -0.6631872 0.5072107 -0.2379377 0.1176265 0.9416180  0.7882518   1.124824
tnde -0.24208214 0.38797292 -0.6239666 0.5326495 -1.0024951 0.5183308 0.7849917  0.3669627   1.679222
pnie -0.05739666 0.08541894 -0.6719431 0.5016199 -0.2248147 0.1100214 0.9442195  0.7986642   1.116302
te   -0.29947881 0.40152620 -0.7458512 0.4557573 -1.0864557 0.4874981 0.7412044  0.3374103   1.628237
pm    0.17757647 0.36243520  0.4899537 0.6241667 -0.5327835 0.8879364        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 can vary over m_cde and c_cond values when interaction = TRUE.

### Re-evaluation at c_cond = cmean
             est        se          Z         p      lower     upper  exp(est) exp(lower) exp(upper)
cde  -0.20016298 0.6777736 -0.2953242 0.7677462 -1.5285749 1.1282489 0.8185973  0.2168445   3.090241
pnde -0.24969887 0.3656050 -0.6829744 0.4946230 -0.9662715 0.4668738 0.7790353  0.3804991   1.595000
tnie -0.07539333 0.1117265 -0.6748026 0.4998012 -0.2943732 0.1435866 0.9273786  0.7449984   1.154407
tnde -0.25395145 0.3598610 -0.7056932 0.4803790 -0.9592661 0.4513632 0.7757295  0.3831740   1.570451
pnie -0.07114074 0.1032713 -0.6888723 0.4909037 -0.2735488 0.1312673 0.9313308  0.7606752   1.140273
te   -0.32509220 0.3761906 -0.8641689 0.3874951 -1.0624122 0.4122278 0.7224607  0.3456211   1.510178
pm    0.20384360 0.3643753  0.5594330 0.5758662 -0.5103190 0.9180061        NA         NA         NA
