Science and Education Publishing American Journal of Medical Sciences and Medicine 2327-6657 1 1 2013 06 15 Identification of Causal Effect with the Non-Compliance and Its EM Algorithm 55 61 EN Li Xiaotong College of Science, China University of Petroleum in Beijing R.P. China Li Sichen AJMSM2013142 10.12691/ajmsm-1-4-2 2013 03 12 2013 06 07 2013 06 15 Many practical studies in biology, medicine, behavior science and the social sciences seek to establish causal relationship between treatments and outcomes, rather than mere associations. In this paper, we use a graphical model to describe a causal graphical model and study its identification. For an unidentifiable model, we introduce covariates which are always observed into the model so that it becomes identifiable. We then give an identifiable condition of the causal graphical model and prove it mathematically. Finally, we give the algorithm for the identifiable average causal effect of outcomes to the accepted treatment and give an example to illustrate this method and algorithm.