HIMA (version 2.2.0)

survHIMA: High-dimensional mediation analysis for survival data

Description

survHIMA is used to estimate and test high-dimensional mediation effects for survival data.

Usage

survHIMA(X, Z, M, OT, status, FDRcut = 0.05, scale = TRUE, verbose = FALSE)

Value

A data.frame containing mediation testing results of selected mediators (FDR <FDPcut).

• ID: index of selected significant mediator.

• alpha: coefficient estimates of exposure (X) --> mediators (M).

• alpha_se: standard error for alpha.

• beta: coefficient estimates of mediators (M) --> outcome (Y) (adjusted for exposure).

• beta_se: standard error for beta

• p.joint: joint p-value of selected significant mediator.

Arguments

X

a vector of exposure.

Z

a matrix of adjusting covariates. Rows represent samples, columns represent variables. Can be NULL.

M

a data.frame or matrix of high-dimensional mediators. Rows represent samples, columns represent mediator variables.

OT

a vector of observed failure times.

status

a vector of censoring indicator (status = 1: uncensored; status = 0: censored)

FDRcut

FDR cutoff applied to define and select significant mediators. Default = 0.05.

scale

logical. Should the function scale the data? Default = TRUE.

verbose

logical. Should the function be verbose? Default = FALSE.

References

Zhang H, Zheng Y, Hou L, Zheng C, Liu L. Mediation Analysis for Survival Data with High-Dimensional Mediators. Bioinformatics. 2021. DOI: 10.1093/bioinformatics/btab564. PMID: 34343267. PMCID: PMC8570823

Examples

if (FALSE) {
data(Example3)
head(Example3$PhenoData)

survHIMA.fit <- survHIMA(X = Example3$PhenoData$Treatment,
                Z = Example3$PhenoData[, c("Sex", "Age")], 
                M = Example3$Mediator, 
                OT = Example3$PhenoData$Time, 
                status = Example3$PhenoData$Status, 
                FDRcut = 0.05,
                scale = FALSE, 
                verbose = TRUE)
survHIMA.fit
}