exercise_input: An example dataset to demonstrate the usage of 'HDMT'

In HDMT: A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses

Description

This example dataset was included to assess the mediation role of DNA methylation in the effect of exercise on prostate cancer progression in a Seattle-based cohort of patients diagnosed with clinically localized PCa. The entire data set contains two sets of p-values from genome-wide testing of 450K CpG sites. Due to space limit, a subset (10 percent) of the full dataset is included in the package for illustration.

The dataset is a matrix containing two columns of p-values for candidate mediators. Column 1 contains the p-values for testing if an exposure is associated with the mediator (alpha!=0). Column 2 contains the p-value for testing if a mediator is associated with the outcome after adjusted for the exposure (beta!=0).

Usage

data("exercise_input")

Format

The format of exercise_input is: num [1:47900, 1:2] 0.4966344 0.1048730 0.1005355 0.4946623 ...

References

James Y. Dai, Janet L. Stanford, Michael LeBlanc. A multiple-testing procedure for high-dimensional mediation hypotheses, Journal of the American Statistical Association, 2020, DOI: 10.1080/01621459.2020.1765785.

Examples

data(exercise_input)
dim(exercise_input)

HDMT documentation built on Jan. 30, 2022, 1:07 a.m.