imphdcox: High dimensional missing data imputation and performing mediation analysis with multivariate
cox proportional hazard model. It works in a multivariate setup.
Description
Given the dimension of variables and survival information the function
performs imputations using missForest function and filters significant variables,
allowing the user to fit multivariate CoxPH model with 5 variables. Further, it performs mediation
analysis among the significant variables and provides handful variables with their alpha.a values
which are mediator model exposure coefficients and beta.a coefficients.
Usage
imphdcox(m, n, survdur, event, time, sig, ths, b, d, data)
Arguments
m
Starting column number from where high dimensional variates to be selected.
n
Ending column number till where high dimensional variates to be selected.
survdur
"Column/Variable name" consisting duration of survival.
event
"Column/Variable name" consisting survival event.
time
"Column/Variable name" consisting time of repeated observations.
sig
Level of significance pre-determined by the user.
ths
A numeric between 0 to 100.
b
Number of MCMC iterations to burn.
d
Number of draws for the iterations.
data
High dimensional data containing survival observations with multiple covariates.
Value
Data frame containing the beta and alpha values of active variables among the significant variables.