unihdma: High dimensional survival analysis using Bayesian univariate...

In autohd: High Dimensional Bayesian Survival Mediation Analysis

Description

Given the dimension of variables and survival information the function filters significant variables allowing the user to perform survival anlaysis with high number of iterations. Further, it performs mediation analysis among the signifiant variables and provides handful variables with their alpha.a values which are mediator model exposure coefficients and beta.a coefficients.

Usage

unihdma(m, n, survdur, event, LC = NULL, t, i, 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.
LC	"Initial time of getting in to the study.
t	A numeric between 0 to 100.
i	Number of MCMC iteration to perform in obtaining posterior extimates of HR by CoxPH.
b	Number of MCMC iterations to burn.
d	Number of draws for the iterations.
data	High dimensional data containing survival observations and high dimensional covariates.

Value

Data frame containing the beta and alpha values of active variables among the significant variables.

Examples

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unihdma(m=8,n=15,survdur="os",event="death",LC="leftcensoring",t=0.02,i=6,b=10,d=10,data=hnscc2)
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autohd documentation built on May 10, 2021, 9:10 a.m.