title: Causal diagrams and multivariate analysis III: confound it!
abstract: This commentary concludes my series concerning inclusion of variables in multivariate analyses. We take up the issues of confounding and effect modification and summarize the work we have thus far done. Finally, we provide a rough algorithm to help guide us through the maze of possibilities that we have outlined.
authors.affiliation: Assistant Professor, Department of Preventive Medicine and Community Health, The University of Texas Medical Branch, Galveston, TX. Electronic address: dajupite@utmb.edu.
authors.forename: Daniel C
authors.initials: DC
authors.lastname: Jupiter
mesh_terms: D000465:Algorithms; D015984:Causality; D015986:Confounding Factors, Epidemiologic; D006801:Humans; D015233:Models, Statistical; D015999:Multivariate Analysis
keywords: confounder; effect modification; multivariate analysis; precision variable