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
DOI: 10.32614/CRAN.package.gma
Author: Yi Zhao, Xi Luo
Maintainer: Yi Zhao <zhaoyi1026 at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: CausalInference
CRAN checks: gma results


Reference manual: gma.pdf


Package source: gma_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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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