Lyons (2011) offered several critiques of the social network analyses of Christakis and Fowler, including issues of confounding, model inconsistency, and statistical dependence in networks. Here we show that in some settings, social network analyses of the type employed by Christakis and Fowler...

Abstract Suppose we are interested in the effect of variable X on variable Y . If X and Y both influence, or are associated with variables that influence, a common outcome, called a collider , then conditioning on the collider (or on a variable influenced by the collider – its “child”)...

Abstract Causal mediation analysis is complicated with multiple effect definitions that require different sets of assumptions for identification. This article provides a systematic explanation of such assumptions. We define five potential outcome types whose means are involved in various effect...

Abstract The paper considers the properties of and relations between confounding and effect modification from the perspective of causal inference and with a distinction drawn as to how each of these two epidemiologic concepts can be defined both with respect to a distribution of potential...

Abstract Interactions measured on the additive scale are more relevant than multiplicative interaction for assessing public health importance and also more closely related to notions of mechanistic synergism. Most work on sample size and power calculations for interaction have focused on the...

Abstract In this tutorial, we provide a broad introduction to the topic of interaction between the effects of exposures. We discuss interaction on both additive and multiplicative scales using risks, and we discuss their relation to statistical models (e.g. linear, log-linear, and logistic...