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Message: [Thought you might ap] [ ] [ ]Send a copy to your email [Send] [Cancel] Your message has been successfully sent to your colleague. [Close Window] Some error has occurred while processing your request. Please try after some time. [Close Window] Export to (*)End Note ( )Procite ( )Reference Manager [ ]Save my selection [Export] [Cancel] Editorials: PDF Only Causal Diagrams for Epidemiologic Research Greenland, Sander; Pearl, Judea; Robins, James M. Author Information Department of Epidemiology, UCLA School of Public Health, Los Angeles, CA; Cognitive Systems Laboratory, Computer Science Department, UCLA School of Engineering, Los Angeles, CA; and Departments of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, MA. Epidemiology: January 1999 - Volume 10 - Issue 1 - p 37-48 * Free Abstract Causal diagrams have a long history of informal use and, more recently, have undergone formal development for applications in expert systems and robotics. We provide an introduction to these developments and their use in epidemiologic research. Causal diagrams can provide a starting point for identifying variables that must be measured and controlled to obtain unconfounded effect estimates. They also provide a method for critical evaluation of traditional epidemiologic criteria for confounding. In particular, they reveal certain heretofore unnoticed shortcomings of those criteria when used in considering multiple potential confounders. We show how to modify the traditional criteria to correct those shortcomings. (Epidemiology 1999;10:37-48) (c) 1999 Lippincott Williams & Wilkins, Inc. Source Causal Diagrams for Epidemiologic Research Epidemiology10(1):37-48, January 1999. * Full-Size * Email * + Favorites * Export * View in Gallery Email to Colleague Colleague's E-mail is Invalid Your Name: (optional) [ ] Your Email: [ ] Colleague's Email: [ ] Separate multiple e-mails with a (;). 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