cmf: Coordinate-wise Mediation Filter

In cmfilter: Coordinate-Wise Mediation Filter

Description

This function performs CMF on a set of potential mediators, given an input and an output variable. It selects those mediators that are deemed relevant by a default or a user-defined decision function, *conditional* on the other mediators in the model. By doing this cyclically, and with multiple random starts, the algorithm outputs an estimate of the best mediators.

Usage

cmf(x, M, y, decisionFunction = "prodcoef", nStarts = 1000,
  nCores = "auto", cutoff = 0.5, maxIter = 25, stableLag = 5,
  pb = TRUE, ...)

Arguments

x	exogenous variable; numeric vector or data frame with x, y, and at least one M column
M	potential mediators; data frame with column names
y	outcome variable; numeric vector
decisionFunction	either a function with as inputs x, m, y, parameters, and as output a TRUE (include) or FALSE (exclude) statement or a string indicating the built-in decision function to use (see details)
nStarts	how many times to start the algorithm
nCores	how many threads (cores) to use for parallel processing
cutoff	a cutoff value for selection: variables are selected if they display a selection rate higher than this value. Only relevant when multiple starts are specified. Can also be specified post-hoc using setCutoff.
maxIter	the maximum number of iterations for each start
stableLag	how long does the selection need to be stable before deciding the algorithm has converged
pb	Whether to display a progress bar (default TRUE). Only available with built-in decision functions
...	parameters passed to decisionFunction

Details

Available decision functions. These functions are implemented in C++ to speed up computation. Between brackets the additional parameter that may be passed to the function in the ... argument of this function. (arguments = defaultvalue):

- prodcoef (p.value = 0.1): Test for the product of coefficients, Sobel test

- causalsteps (p.value = 0.1): Causal steps test min(Ta, Tb)

Value

an object of class cmf. See cmf-methods

Examples

# generate some data
dat <- generateMed(a = (1:10)/20, b = (1:10)/20)
# Run CMF on this data
cmf(dat)

cmfilter documentation built on April 11, 2019, 5:07 p.m.