### Mediator model Call: lm(formula = bili ~ trt, data = data) Residuals: Min 1Q Median 3Q Max -3.4000 -2.5000 -1.7000 0.4434 24.3000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.2132 0.8784 2.520 0.0123 * trt 0.7434 0.5532 1.344 0.1801 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 4.594 on 274 degrees of freedom Multiple R-squared: 0.006548, Adjusted R-squared: 0.002923 F-statistic: 1.806 on 1 and 274 DF, p-value: 0.1801 ### Outcome model Call: survival::coxph(formula = Surv(time, status) ~ trt + bili, data = data, ties = "efron") n= 276, number of events= 129 coef exp(coef) se(coef) z Pr(>|z|) trt -0.23318 0.79201 0.17984 -1.297 0.195 bili 0.14225 1.15287 0.01335 10.659 <2e-16 *** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 exp(coef) exp(-coef) lower .95 upper .95 trt 0.792 1.2626 0.5567 1.127 bili 1.153 0.8674 1.1231 1.183 Concordance= 0.77 (se = 0.02 ) Likelihood ratio test= 75.15 on 2 df, p=<2e-16 Wald test = 113.8 on 2 df, p=<2e-16 Score (logrank) test = 157.9 on 2 df, p=<2e-16 ### Mediation analysis est se Z p lower upper exp(est) cde -0.2798107 0.21580300 -1.2966023 0.1947681 -0.70277676 0.1431554 0.7559269 pnde -0.2798107 0.21580300 -1.2966023 0.1947681 -0.70277676 0.1431554 0.7559269 tnie 0.1268956 0.09517082 1.3333460 0.1824183 -0.05963575 0.3134270 1.1352985 tnde -0.2798107 0.21580300 -1.2966023 0.1947681 -0.70277676 0.1431554 0.7559269 pnie 0.1268956 0.09517082 1.3333460 0.1824183 -0.05963575 0.3134270 1.1352985 te -0.1529150 0.23404125 -0.6533679 0.5135192 -0.61162745 0.3057974 0.8582026 pm -0.7212813 1.46382965 -0.4927358 0.6221993 -3.59033469 2.1477721 NA exp(lower) exp(upper) cde 0.4952083 1.153909 pnde 0.4952083 1.153909 tnie 0.9421076 1.368106 tnde 0.4952083 1.153909 pnie 0.9421076 1.368106 te 0.5424673 1.357707 pm NA NA Evaluated at: avar: trt a1 (intervened value of avar) = 2.3 a0 (reference value of avar) = 1.1 mvar: bili 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.