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  • Avin, C., Shpitser, I., & Pearl, J. (2005). Identifiability of path-specific effects. In proceedings of the 19th international joint conference on artificial intelligence (Vol. 19, pp. 357363). San Francisco: Morgan Kauffman.
  • Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychology research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 11731182.
  • Conger Jr., R. D., Elder, G. H., Lorenz, F. O., Conger, F. J., Simons, R. L., & Whitbeck, L. B., et al. (1990). Linking economic hardship to marital quality and instability. Journal of Marriage and the Family, 52, 643656.
  • Doll, R., & Hill, A. B. (1950). Smoking and carcinoma of the lung. BMJ, 2, 739748.
  • Eagly, A. H., & Chaiken, S. (1993). The psychology of attitudes. Fort Worth, TX: Harcourt Brace Jovanovich.
  • Huang, Y., & Valtorta, M. (2006). Pearl's calculus of interventions is complete. In Proceedings of the twenty-second annual conference on uncertainty in artificial intelligence (UAI-06) (pp. 217224). Arlington, VA: AUAI Press.
  • Imai, K., Tingley, D., & Yamamoto T. (2013). Experimental designs for identifying causal mechanisms. Journal of the Royal Statistical Society, series (A), 176(1), 551.
  • Judd, C. M., & Kenny, D. A. (1981). Process analysis: Estimating mediation in treatment evaluation. Evaluation Review, 5, 602619.
  • Kaufman, J. S., MacLehose, R. F., & Kaufman, S. (2004). A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiologic Perspectives and Innovations, 1(4), 113.
  • MacKinnon, D., & Dwyer, J. (1993). Estimating mediated effects in prevention studies. Evaluation Review, 17(2), 144158.
  • MacKinnon, D. P., Warsi, D. P., & Dwyer, J. (1995). A simulation study of mediated effect measures. Multivariate Behavioral Research, 30, 4165.
  • Neyman, J. (1923). Sur les applications de la thar des probabilities aux experiences agaricales: Essay des principle. Excerpts reprinted (1990) in english. Statistical Science, 5, 463472.
  • Pearl, J. (1988). Probabilistic reasoning in intelligent systems. San Mateo, CA: Morgan and Kaufmann.
  • Pearl, J. (2000). Causality: Models, reasoning, and inference. Cambridge, UK: Cambridge University Press.
  • Pearl, J. (2001). Direct and indirect effects. In Proceedings of the seventeenth conference annual conference on uncertainty in artificial intelligence (UAI-01) (pp. 411420). San Francisco: Morgan Kaufmann.
  • Pearl, J. (2011). The causal mediation formula—a guide to the assessment of pathways and mechanisms (Tech. Rep. No. R-379). Los Angeles: Cognitive Systems Laboratory, University of California.
  • Richardson, T. S. (2009). A factorization criterion for acyclic directed mixed graphs. In Proceedings of the twenty-fifth annual conference on uncertainty in artificial intelligence (UAI-09) (pp. 463470). Corvallis, OR: AUAI Press.
  • Richardson, T. S., Robins, J. M., & Shpitser, I. (2012). Nested markov properties for acyclic directed mixed graphs. In Proceedings of the twenty-fifth conference annual conference on uncertainty in artificial intelligence (UAI-12) (pp. 1313). Corvallis, OR: AUAI Press.
  • Robins, J. (1986). A new approach to causal inference in mortality studies with sustained exposure periods – application to control of the healthy worker survivor effect. Mathematical Modeling, 7, 13931512.
  • Robins, J. M., & Greenland, S. (1992). Identifiability and exchangeability of direct and indirect effects. Epidemiology, 3, 143155.
  • Robins, J. M., Hernan, M., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550560.
  • Robins, J. M., & Richardson, T. S. (2010). Alternative graphical causal models and the identification of direct effects. In P. Shrout et al. (Eds.), Causality and psychopathology: Finding the determinants of disorders and their cures (pp. 152). New York: Oxford University Press.
  • Robins, J. M., & Wasserman, L. (1997). Estimation of effects of sequential treatments by reparameterizing directed acyclic graphs. In Proceedings of the 13th annual conference on uncertainty in artificial intelligence (UAI-97) (pp. 409420). San Francisco: Morgan Kaufmann.
  • Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and non-randomized studies. Journal of Educational Psychology, 66, 688701.
  • Rucker, D. D., Preacher, K. J., Tormala, Z. L., & Petty, R. E. (2011). Mediation analysis in social psychology: Current practices and new recommendations. Social and Personality Psychology Compass, 5/6, 359371.
  • Schwarz, N., Bless, H., Strack, F., Klumpp, G., Rittenauer-Schatka, H., & Simons, A. (1991). Ease of retrieval as information: Another look at the availability heuristic. Journal of Personality and Social Psychology, 61, 195202.
  • Shpitser, I., & Pearl, J. (2006a). Identification of conditional interventional distributions. In R. Dechter and T.S. Richardson (Eds.), Proceedings of the twenty-second conference on uncertainty in artificial intelligence (UAI-06) (pp. 437444). Corvallis, OR: AUAI Press.
  • Shpitser, I., & Pearl, J. (2006b). Identification of joint interventional distributions in recursive semi-markovian causal models. In Proceedings of the 21st national conference on artificial intelligence (AAAI 06) (pp. 12191226). Palo Alto, CA: AAAI Press.
  • Shpitser, I., & Pearl, J. (2008). Complete identification methods for the causal hierarchy. Journal of Machine Learning Research, 9, 19411979.
  • Shpitser, I., Richardson, T. S., & Robins, J. M. (2011). An efficient algorithm for computing interventional distributions in latent variable causal models. In Cozman, Fabio Gagliardi and Pfeffer, Avi (Eds), Proceedings of the twenty seventh conference on uncertainty in artificial intelligence (UAI-11) (pp. 661670). Corvallis, OR: AUAI Press.
  • Tchetgen, E. J. T., & Shpitser, I. (2012b). Semiparametric theory for causal mediation analysis: Efficiency bounds, multiple robustness, and sensitivity analysis. Annals of Statistics, Ann. Statist. 40(3), 18161845.
  • Tian, J., & Pearl, J. (2002a). A general identification condition for causal effects. In Proceedings of the eighteenth national conference on artificial intelligence (AAAI 02) (pp. 567573). Menlo Park, CA: American Association for Artificial Intelligence.
  • Tian, J., & Pearl, J. (2002b). On the testable implications of causal models with hidden variables. In Proceedings of the eighteenth conference on uncertainty in artificial intelligence (UAI-02) (pp. 519527). San Francisco: Morgan Kaufmann.
  • Tormala, Z. L., Briñol, P., & Petty, R. E. (2007a). Multiple roles for source credibility under high elaboration: It's all in the timing. Social Cognition, 25, 536552.
  • Tormala, Z. L., Falces, C., Briñol, P., & Petty, R. E. (2007b). Ease of retrieval effects in social judgement: The role of unrequested cognitions. Journal of Personality and Social Psychology, 93, 143157.
  • VanderWeele, T. J., Asomaning, K., Tchetgen, E. J. T., Han, Y., Spitz, M. R., Shete, S., et al. (2012). Genetic variants on 15q25.1, smoking, and lung cancer: An assessment of mediation and interaction. American Journal of Epidemiology, 175(10), 10131020.
  • VanderWeele, T. J., & Vansteelandt, S. (2009). Conceptual issues concerning mediation, intervention, and composition. Statistics and Its Interface (Special Issue on Mental Health and Social Behavioral Science), 2, 457468.
  • Verma, T. S., & Pearl, J. (1990). Equivalence and synthesis of causal models (Tech. Rep. No. R-150). Los Angeles: Department of Computer Science, University of California.
  • Woodworth, R. S. (1928). Dynamic psychology. In C. Murchison (Ed.), Psychologies of 1925. Worcester, MA: Clark University Press.
  • Word, C., Zanna, M., & Cooper, J. (1974). The nonverbal mediation of self-fulfilling prophecies in interracial interaction. Journal of Experimental Social Psychology, 10, 109120.
  • Wright, S. (1921). Correlation and causation. Journal of Agricultural Research, 20, 557585.