### Mediator model Call: glm(formula = bili_bin ~ trt + age + male + stage, family = binomial(link = "logit"), data = data) 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 5.03e-06 *** --- 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: survival::survreg(formula = Surv(time, status) ~ trt + bili_bin + age + male + stage, data = data, dist = "exponential") Value Std. Error z p (Intercept) 11.50056 0.62359 18.44 < 2e-16 trt 0.10094 0.17952 0.56 0.574 bili_bin -1.41562 0.20843 -6.79 1.1e-11 age -0.01785 0.00894 -2.00 0.046 male -0.02263 0.24269 -0.09 0.926 stage -0.51456 0.12771 -4.03 5.6e-05 Scale fixed at 1 Exponential distribution Loglik(model)= -1155.4 Loglik(intercept only)= -1206.3 Chisq= 101.72 on 5 degrees of freedom, p= 2.3e-20 Number of Newton-Raphson Iterations: 5 n= 276 ### Mediation analysis est se Z p lower upper exp(est) cde 0.12113036 0.2154291 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 pnde 0.12113036 0.2154291 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 tnie 0.06735285 0.1016439 0.6626357 0.5075639 -0.1318654 0.2665712 1.069673 tnde 0.12113036 0.2154291 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 pnie 0.06735285 0.1016439 0.6626357 0.5075639 -0.1318654 0.2665712 1.069673 te 0.18848321 0.2379104 0.7922446 0.4282181 -0.2778126 0.6547790 1.207417 pm 0.37916293 0.5393986 0.7029365 0.4820953 -0.6780388 1.4363647 NA exp(lower) exp(upper) cde 0.7400016 1.721789 pnde 0.7400016 1.721789 tnie 0.8764589 1.305480 tnde 0.7400016 1.721789 pnie 0.8764589 1.305480 te 0.7574388 1.924717 pm 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) cde 0.12113036 0.21542910 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 pnde 0.12113036 0.21542910 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 tnie 0.06098719 0.09173287 0.6648346 0.5061563 -0.1188059 0.2407803 1.062885 tnde 0.12113036 0.21542910 0.5622748 0.5739288 -0.3011029 0.5433636 1.128772 pnie 0.06098719 0.09173287 0.6648346 0.5061563 -0.1188059 0.2407803 1.062885 te 0.18211755 0.23390702 0.7785895 0.4362216 -0.2763318 0.6405669 1.199755 pm 0.35535077 0.52324932 0.6791232 0.4970598 -0.6701990 1.3809006 NA exp(lower) exp(upper) cde 0.7400016 1.721789 pnde 0.7400016 1.721789 tnie 0.8879801 1.272242 tnde 0.7400016 1.721789 pnie 0.8879801 1.272242 te 0.7585612 1.897556 pm NA NA