TY - JOUR
T1 - Dynamic GSCA (Generalized Structured Component Analysis) with Applications to the Analysis of Effective Connectivity in Functional Neuroimaging Data
AU - Jung, Kwanghee
AU - Takane, Yoshio
AU - Hwang, Heungsun
AU - Woodward, Todd S.
N1 - Copyright:
Copyright 2012 Elsevier B.V., All rights reserved.
PY - 2012/10
Y1 - 2012/10
N2 - We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also incorporates direct and modulating effects of input variables on specific latent variables and on connections between latent variables, respectively. An alternating least square (ALS) algorithm is developed for parameter estimation. An improved bootstrap method called a modified moving block bootstrap method is used to assess reliability of parameter estimates, which deals with time dependence between consecutive observations effectively. We analyze synthetic and real data to illustrate the feasibility of the proposed method.
AB - We propose a new method of structural equation modeling (SEM) for longitudinal and time series data, named Dynamic GSCA (Generalized Structured Component Analysis). The proposed method extends the original GSCA by incorporating a multivariate autoregressive model to account for the dynamic nature of data taken over time. Dynamic GSCA also incorporates direct and modulating effects of input variables on specific latent variables and on connections between latent variables, respectively. An alternating least square (ALS) algorithm is developed for parameter estimation. An improved bootstrap method called a modified moving block bootstrap method is used to assess reliability of parameter estimates, which deals with time dependence between consecutive observations effectively. We analyze synthetic and real data to illustrate the feasibility of the proposed method.
KW - a modified moving block bootstrap method
KW - alternating least squares (ALS) algorithm
KW - effective connectivity
KW - functional neuroimaging
KW - generalized structured component analysis (GSCA)
KW - longitudinal and time series data
KW - structural equation modeling (SEM)
UR - http://www.scopus.com/inward/record.url?scp=84867858728&partnerID=8YFLogxK
U2 - 10.1007/s11336-012-9284-2
DO - 10.1007/s11336-012-9284-2
M3 - Article
AN - SCOPUS:84867858728
VL - 77
SP - 827
EP - 848
JO - Psychometrika
JF - Psychometrika
SN - 0033-3123
IS - 4
ER -