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Full-Text Articles in Epidemiology
On The Definition Of A Confounder, Tyler J. Vanderweele, Ilya Shpitser
On The Definition Of A Confounder, Tyler J. Vanderweele, Ilya Shpitser
COBRA Preprint Series
The causal inference literature has provided a clear formal definition of confounding expressed in terms of counterfactual independence. The causal inference literature has not, however, produced a clear formal definition of a confounder, as it has given priority to the concept of confounding over that of a confounder. We consider a number of candidate definitions arising from various more informal statements made in the literature. We consider the properties satisfied by each candidate definition, principally focusing on (i) whether under the candidate definition control for all "confounders" suffices to control for "confounding" and (ii) whether each confounder in some context …
Components Of The Indirect Effect In Vaccine Trials: Identification Of Contagion And Infectiousness Effects, Tyler J. Vanderweele, Eric J. Tchetgen, M. Elizabeth Halloran
Components Of The Indirect Effect In Vaccine Trials: Identification Of Contagion And Infectiousness Effects, Tyler J. Vanderweele, Eric J. Tchetgen, M. Elizabeth Halloran
COBRA Preprint Series
Vaccination of one person may prevent the infection of another either because (i) the vaccine prevents the first from being infected and from infecting the second or because (ii) even if the first person is infected, the vaccine may render the infection less infectious. We might refer to the first of these mechanisms as a contagion effect and the second as an infectiousness effect. In this paper, for the simple setting of a randomized vaccine trial with households of size two, we use counterfactual theory under interference to provide formal definitions of a contagion effect and an infectiousness effect. Using …
On The Nondifferential Misclassification Of A Binary Confounder, Elizabeth L. Ogburn, Tyler J. Vanderweele
On The Nondifferential Misclassification Of A Binary Confounder, Elizabeth L. Ogburn, Tyler J. Vanderweele
COBRA Preprint Series
Abstract Consider a study with binary exposure, outcome, and confounder, where the confounder is nondifferentially misclassified. Epidemiologists have long accepted the unproven but oft-cited result that, if the confounder is binary, odds ratios, risk ratios, and risk differences which control for the mismeasured confounder will lie between the crude and the true measures. In this paper the authors provide an analytic proof of the result in the absence of a qualitative interaction between treatment and confounder, and demonstrate via counterexample that the result need not hold when there is a qualitative interaction between treatment and confounder. They also present an …