R package 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.
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References in zbMATH (referenced in 3 articles , 1 standard article )
Showing results 1 to 3 of 3.
- Zhang, Xiaoke; Xue, Wu; Wang, Qiyue: Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies (2021)
- Zhao, Yi; Luo, Xi: Granger mediation analysis of multiple time series with an application to functional magnetic resonance imaging (2019)
- Yi Zhao, Xi Luo: Granger Mediation Analysis of Multiple Time Series with an Application to fMRI (2017) arXiv