A Time and Place for Causal Inference Methods in Perinatal and Paediatric Epidemiology

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Paediatric and Perinatal Epidemiology


In this issue of Paediatric and Perinatal Epidemiology, Sudan et al. describe their analysis of cell phone exposure and hearing loss among children enrolled in the Danish National Birth Cohort. Sudan and colleagues have provided a thoughtful analysis and incorporated several relatively new analytic methods. These include the use of directed acyclic graphs (DAGs), marginal structural models (MSM), and doubly robust estimators (DRE). In addition, the authors also present results from a sensitivity analyses for unmeasured confounding and outcome misclassification. While we applaud their efforts, we would like to provide a rationale for the use – and misuse – of these and other methods for causal inference.


Published in 2013. This article is a U.S. Government work and is in the public domain in the USA. This work was supported by the Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health.