StepThree function

Post-hoc model

An auxiliary function which generates p-value based on outcome and mediation model.

StepThree(X, M, C, time, status, X_sel_Y_s1, M_X_sel_s2)

Arguments

• X: An n by p matrix of exposures.
• M: An n by p matrix of mediators.
• C: An n by p matrix of covariates. If there are no covariates, set C = NULL.
• time: A vector of survival time of samples.
• status: A vector of status indicator: 0=alive, 1=dead.
• X_sel_Y_s1: Outputs from StepOne: A vector of selected X for Y.
• M_X_sel_s2: Outputs from StepTwo: A data table with selected M, X pairs and related effect size.

Returns

A list with the following components: - p_beta_m: p-values generated from outcome model

• p_alpha_x: p-values generated from mediation modell

• outcome_model: coefficient estimates from outcome model

• med_results: coefficient estimates from mediation model

Examples

data(example_dat)
surv_dat <- example_dat$surv_dat
res_step1 <- StepOne(X = example_dat$X, M = example_dat$M, time = surv_dat$time,
status = surv_dat$status, model_option = "MCP")
M_X_sel_s2 <- StepTwo(X = example_dat$X, M = example_dat$M, time = surv_dat$time,
status = surv_dat$status, X_sel_Y_s1 = res_step1$X_sel_Y_s1, M_X_s1 = res_step1$M_X_s1,
M_sel_Y_s1 = res_step1$M_sel_Y_s1)
res_step3 <- StepThree(X = example_dat$X, M = example_dat$M, C = example_dat$C,
time = surv_dat$time, status = surv_dat$status, X_sel_Y_s1 = res_step1$X_sel_Y_s1,
M_X_sel_s2 = M_X_sel_s2)