In this journal club episode, we discuss one of our top 10 favourite epidemiology papers: “Does obesity shorten life? The importance of well-defined interventions to answer causal questions” by Miguel Hernán and Sarah Taubman. We talk about the consistency assumption in causal inference, why we think measurement error needs to be added to the list of assumptions for causal inference, and invent a new word (“statisticalize”) to dismiss the notion that fancy methods can always solve our problems.

 

References:

Hernán MA, Taubman SL. Does obesity shorten life? The importance of well-defined interventions to answer causal questions. Int J Obes. 2008;32:s8-s14.

Cole S, Frangakis C. The consistency statement in causal inference: a definition or an assumption? Epidemiology. 2009; 20:3-5.