### Mediator model Call: glm(formula = bili_bin ~ trt, family = binomial(link = "logit"), data = data) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 0.08577 0.38245 0.224 0.823 trt -0.08577 0.24091 -0.356 0.722 (Dispersion parameter for binomial family taken to be 1) Null deviance: 382.49 on 275 degrees of freedom Residual deviance: 382.36 on 274 degrees of freedom AIC: 386.36 Number of Fisher Scoring iterations: 3 ### Outcome model Call: MASS::glm.nb(formula = platelet ~ trt + bili_bin, data = data, init.theta = 7.759836932, link = log) Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 5.59812 0.07330 76.368 < 2e-16 *** trt 0.02040 0.04387 0.465 0.64190 bili_bin -0.13003 0.04388 -2.963 0.00304 ** --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 (Dispersion parameter for Negative Binomial(7.7598) family taken to be 1) Null deviance: 291.56 on 275 degrees of freedom Residual deviance: 282.41 on 273 degrees of freedom AIC: 3281.8 Number of Fisher Scoring iterations: 1 Theta: 7.760 Std. Err.: 0.669 2 x log-likelihood: -3273.795 ### Mediation analysis est se Z p lower upper exp(est) cde 0.02448142 0.052643871 0.4650383 0.6419040 -0.07869867 0.12766151 1.024784 pnde 0.02448142 0.052643871 0.4650383 0.6419040 -0.07869867 0.12766151 1.024784 tnie 0.00333063 0.009408267 0.3540110 0.7233307 -0.01510923 0.02177049 1.003336 tnde 0.02448142 0.052643871 0.4650383 0.6419040 -0.07869867 0.12766151 1.024784 pnie 0.00333063 0.009408267 0.3540110 0.7233307 -0.01510923 0.02177049 1.003336 te 0.02781205 0.053454381 0.5202950 0.6028580 -0.07695662 0.13258071 1.028202 pm 0.12122598 0.377371877 0.3212374 0.7480305 -0.61840931 0.86086126 NA exp(lower) exp(upper) cde 0.9243184 1.136168 pnde 0.9243184 1.136168 tnie 0.9850043 1.022009 tnde 0.9243184 1.136168 pnie 0.9850043 1.022009 te 0.9259300 1.141771 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: c_cond (covariate vector value) = Note that effect estimates do not vary over m_cde and c_cond values when interaction = FALSE.