gma: Granger Mediation Analysis

Performs Granger mediation analysis (GMA) for time series. This package includes a single level GMA model and a two-level GMA model, for time series with hierarchically nested structure. The single level GMA model for the time series of a single participant performs the causal mediation analysis which integrates the structural equation modeling and the Granger causality frameworks. A vector autoregressive model of order p is employed to account for the spatiotemporal dependencies in the data. Meanwhile, the model introduces the unmeasured confounding effect through a nonzero correlation parameter. Under the two-level model, by leveraging the variabilities across participants, the parameters are identifiable and consistently estimated based on a full conditional likelihood or a two-stage method. See Zhao, Y., & Luo, X. (2017), Granger Mediation Analysis of Multiple Time Series with an Application to fMRI, <doi:10.48550/arXiv.1709.05328> for details.

Version:	1.0
Depends:	MASS, nlme, car
Published:	2017-09-19
Author:	Yi Zhao, Xi Luo
Maintainer:	Yi Zhao <zhaoyi1026 at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
In views:	CausalInference
CRAN checks:	gma results

Documentation:

Reference manual:

gma.pdf

Downloads:

Package source:	gma_1.0.tar.gz
Windows binaries:	r-devel: gma_1.0.zip, r-release: gma_1.0.zip, r-oldrel: gma_1.0.zip
macOS binaries:	r-release (arm64): gma_1.0.tgz, r-oldrel (arm64): gma_1.0.tgz, r-release (x86_64): gma_1.0.tgz, r-oldrel (x86_64): gma_1.0.tgz

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