Granger Causality Testing with Intensive Longitudinal Data

• Published in: Prevention science Vol. 20; no. 3; pp. 442 - 451
• Main Author: Molenaar, Peter C. M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.04.2019; Springer Nature B.V
• Subjects: Biophysics; Causality; Child and School Psychology; Coherence; Cointegration analysis; Criteria; Data; Derivation; Economic models; Health Psychology; Longitudinal Studies; Medicine; Medicine & Public Health; Models, Theoretical; Networks; Numbers; Prevention; Prospects; Psychopathology; Public Health; Regression analysis; Representation; Time; Variables; Partial directed coherence; Standard VAR; Hybrid VAR; Structural VAR; Granger causality

The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic netwo...