conditional  methods  of adjustment  are often used to quantify  the effect  of the exposure on the outcome.  as  a  result,  the  stratums-specific  risk  ratio  estimates  are  reported  in  the  presence  of interaction   between   exposure  and  confounder(s)   in  the  literature,  even  if  the  target  of  the intervention on the exposure is the total population and the interaction itsel...

This paper concerns the assessment of the effects of actions from a combination of nonexperimental data and causal assumptions encoded in the form of a directed acyclic graph in which some variables are presumed to be unobserved. We provide a procedure that systematically identifies cause effects between two sets of variables conditioned on some other variables, in time polynomial in the number...

Available online at: http://jbe.tums.ac.ir Conditional methods of adjustment are often used to quantify the effect of the exposure on the outcome. As a result, the stratums-specific risk ratio estimates are reported in the presence of interaction between exposure and confounder(s) in the literature, even if the target of the intervention on the exposure is the total population and the interacti...

In this paper we present a new approach to reason about actions and causation which is based on a conditional logic. The conditional implication is interpreted as causal implication. This makes it possible to formalize in a uniform way causal dependencies between actions and their immediate and indirect effects. Furthermore, this new approach provides a natural formalization of concurrent actio...

Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?") is important to fault diagnosis, planning, de­ termination of liability, and policy analysis. We present a method for evaluating counter­ factuals when the underlying causal model is represented by structural models a nonlin­ ear generalization of the simultaneous equa­ tions models commonly used in econometr...

Structural causal models offer a popular framework for exploring causal concepts. However, due to their limited expressiveness, structural models have difficulties coping with such concepts as actual (event-to-event) causation. In this paper, we propose a new type of causal model, based on embedding structural considerations in the language of situation calculus. By using situation calculus as ...

In two recent communications, Cole and Frangakis and VanderWeele conclude that the consistency rule used in causal inference is an assumption that precludes any side-effects of treatment/exposure on the outcomes of interest. They further develop auxiliary notation to make this assumption formal and explicit. I argue that the consistency rule is a theorem in the logic of counterfactuals and need...

We propose a new inference rule for estimating causal structure that underlies the observed statistical dependencies among n random variables. Our method is based on comparing the conditional distributions of variables given their direct causes (the so-called “Markov kernels”) for all hypothetical causal directions and choosing the most plausible one. We consider those Markov kernels most plaus...