get_perm_pval: Function that calculate permutation-based p-values for...

In wesleycrouse/bmediatR: Toolset for running Bayesian mediation model selection analysis

Function that calculate permutation-based p-values for posterior odds

Description

This function takes posterior odds results from bmediatR() and calculates permutation p-values based on permuting the mediator.

Usage

get_perm_pval(
  y,
  M,
  X,
  Z = NULL,
  w = NULL,
  model_type = c("mediation", "partial", "complete", "colocal"),
  ln_prior_c = "complete",
  num_perm = 1000,
  verbose = FALSE,
  ...
)

Arguments

y	Vector or single column matrix of an outcome variable. Single outcome variable expected. Names or rownames must match across M and X, and Z and w (if provided).
M	Vector or matrix of mediator variables. Multiple mediator variables are supported. Names or rownames must match across y and X, and Z and w (if provided).
X	Design matrix of the driver. Names or rownames must match across y and M, and Z and w (if provided). One common application is for X to represent genetic information at a QTL as either founder strain haplotypes in a multiparental population or variant genotypes, though it is generalizable to types of variables.
Z	DEFAULT: NULL. Design matrix of covariates that influence the outcome variable. Names or rownames must match across y, M and X, and w (if provided).
w	DEFAULT: NULL. Vector of weights for individuals in analysis. Names or rownames must match across y, M X, and Z (if provided). A common use would be for an analysis of strain means, where w would be a vector of the number of individuals per strain. If no w is given, observations are equally weighted as 1.

Examples

get_perm_pval()

wesleycrouse/bmediatR documentation built on April 28, 2023, 4:01 p.m.