Detecting Causal Relations in the Presence of Unmeasured Variables
  The presence of latent variables can greatly complicate inferences about
causal relations between measured variables from statistical data. In many
cases, the presence of latent variables makes it impossible to determine for
two measured variables A and B, whether A causes B, B causes A, or there is
some common cause. In this paper I present several theorems that state
conditions under which it is possible to reliably infer the causal relation
between two measured variables, regardless of whether latent variables are
acting or not.
