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, <arXiv:1709.05328> for details.

Package details

AuthorYi Zhao <zhaoyi1026@gmail.com>, Xi Luo <xi.rossi.luo@gmail.com>
MaintainerYi Zhao <zhaoyi1026@gmail.com>
LicenseGPL (>= 2)
Version1.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("gma")

Try the gma package in your browser

Any scripts or data that you put into this service are public.

gma documentation built on May 2, 2019, 6:08 a.m.