Using directed acyclic graphs to detect limitations of traditional regression in longitudinal studies

International Journal of Public Health

Volumn 55, Issue 6, 2010, Pages 701-703

  Moodie, Erica E M ^b   Stephens, D A ^a  

^a MCGILL UNIVERSITY   (Canada)

^b NONE

Author keywords

Confounding; Directed acyclic graphs; Longitudinal data; Mediation

Indexed keywords

ARTICLE; COMPUTER GRAPHICS; CROSS-SECTIONAL STUDY; EPIDEMIOLOGY; LONGITUDINAL STUDY; PUBLIC HEALTH; STATISTICAL MODEL;

BIAS (EPIDEMIOLOGY); CAUSALITY; COMPUTER GRAPHICS; CONFOUNDING FACTORS (EPIDEMIOLOGY); CROSS-SECTIONAL STUDIES; LONGITUDINAL STUDIES; MODELS, STATISTICAL; PUBLIC HEALTH;

EID: 79951958211     PISSN: 16618556     EISSN: 1420911X     Source Type: Journal    
DOI: 10.1007/s00038-010-0184-x     Document Type: Article

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