bayesIndirect: bayesIndirect

Description Usage Arguments Value Warning Author(s) References

View source: R/bayesIndirect.R

Description

bayesIndirect examines the indirect effect of a SNP on the outcome through the mediator in a Bayesian framework with a spike and slab prior.

Usage

1
bayesIndirect(x, k, y, z = NULL, nCov = 0, plot0 = FALSE, nIts = 50000, nBurn = 10000, propGamma1Pi = 0.7, cx = 10, pix = 0.5, SEED = 1)

Arguments

x

is the exposure, such as the SNP.

k

is the mediator.

y

is the normally distributed outcome.

z

is the matrix of covariates.

nCov

is the number of covariates. nCov = 0, 1 or 2.

plot0

true if density plot should be outputted or false otherwise.

nIts

is the number of iterations of the MCMC.

nBurn

is the Burn-in period.

propGamma1Pi

is the probability of gamma from the Bernoulli distribution.

cx

is the variance of beta X from the normal distribution.

pix

is the probability that beta x is sampled from the normal distribution.

SEED

is the seed for the SKAT function, default = 1.

Value

The posterior mean, standard deviation and quantiles for each variable.

Warning

library(coda) is needed to run this function.

Author(s)

Sharon Lutz, Annie Thwing

References

Lutz SM, Hokanson JE, Sharma S, Weiss S, Raby B, Lange C. (2013) On the Integration of Expression Profiles in Genetic Association Studies: A Bayesian Approach to Determine the Path from Gene to Disease. Open Journal of Genetics. 3(3).


SharonLutz/bayesIndirect documentation built on May 20, 2018, 11:12 a.m.