Package cfma details

Causal Functional Mediation Analysis

Performs causal functional mediation analysis (CFMA) for functional treatment, functional mediator, and functional outcome. This package includes two functional mediation model types: (1) a concurrent mediation model and (2) a historical influence mediation model. See Zhao et al. (2018), Functional Mediation Analysis with an Application to Functional Magnetic Resonance Imaging Data, for details.

Maintainer: Yi Zhao < zhaoyi1026 at gmail.com >

From within R, enter citation(cfma)

To cite package 'cfma' in publications use:

Yi Zhao, Xi Luo, Martin Lindquist and Brian Caffo (2018). cfma:
Causal Functional Mediation Analysis. R package version 1.0.

A BibTeX entry for LaTeX users is

@Manual{,
title = {cfma: Causal Functional Mediation Analysis},
author = {Yi Zhao and Xi Luo and Martin Lindquist and Brian Caffo},
year = {2018},
note = {R package version 1.0},
}

If you have any problems with this package you can open a new issue or check the already existing ones here.

To install this package, start R and enter:

source("https://neuroconductor.org/neurocLite.R")

# use release_versions() to find previous releases
neuro_install('cfma', release_repo= 'https://neuroconductor.org/releases/2018/feb')

# Default Install
neuro_install('cfma')

# From the Binary Repo in NeuroC
neuro_install('cfma', release = "stable", release_repo = binary_release_repo(release = "stable"))
neuro_install('cfma', release = "current", release_repo = binary_release_repo(release = "current"))

# from GitHub
neuro_install('cfma', release = "stable", release_repo = "github")
neuro_install('cfma', release = "current", release_repo = "github")

More detailed installation instructions can be found here.