On Probabilistic Multifactor Potential Outcome Models
Daniel Berglund, Timo Koski · KTH Publication Database DiVA (KTH Royal Institute of Technology) · 2019
The sufficient cause framework describes how sets of sufficient causes are responsible for causing some event or outcome. It is known that it is closely connected with Boolean functions. In this paper we define this relation formally, and show how it can be used together with Fourier expansion of the Boolean functions to lead to new insights. The main result is a probibalistic version of the multifactor potential outcome model based on independence of causal influence models and Bayesian networks.