How multiple causes combine: independence constraints on causal inference.

ABSTRACT: According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to c

SUBMITTER: Liljeholm M 

PROVIDER: S-EPMC4530320 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature