Alternative monotonicity assumptions for improving bounds on natural direct effects

International Journal of Biostatistics

Volumn 9, Issue 2, 2013, Pages 235-249

  Chiba, Yasutaka ^a   Taguri, Masataka ^b  

^a KINKI UNIVERSITY SCHOOL OF MEDICINE   (Japan)

^b YOKOHAMA CITY UNIVERSITY   (Japan)

Author keywords

Causal inference; Mediation; Potential outcome; Randomized trial

Indexed keywords

ANALYTIC METHOD; ARTICLE; CONTROLLED DIRECT EFFECT; HUMAN; ISCHEMIC HEART DISEASE; MEDIATOR; MONOTONICITY ASSUMPTION; NATURAL DIRECT EFFECT; OUTCOME ASSESSMENT; OUTCOME VARIABLE; RANDOMIZED CONTROLLED TRIAL (TOPIC); SYSTEM ANALYSIS; THERAPY EFFECT; TREATMENT INDICATION; BIOMETRY; CORONARY DISEASE; EPIDEMIOLOGY; HYPERLIPIDEMIAS; PROCEDURES; TREATMENT OUTCOME;

COLESTYRAMINE;

BIOMETRY; CAUSALITY; CHOLESTYRAMINE RESIN; CORONARY DISEASE; HUMANS; HYPERLIPIDEMIAS; RANDOMIZED CONTROLLED TRIALS AS TOPIC; TREATMENT OUTCOME;

EID: 84898646617     PISSN: None     EISSN: 15574679     Source Type: Journal    
DOI: 10.1515/ijb-2012-0022     Document Type: Article

References (22)

1. Robins JM, Greenland S. Identifiability and exchangeability for direct and indirect effects. Epidemiology 1992;3:143-55.
2. Pearl J. Direct and indirect effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence, Morgan Kaufmann, San Francisco, 2001:411-20.
3. Robins JM. Semantics of causal DAG models and the identification of direct and indirect effects. In Green PJ, Hjort NL, Richardson S, editors. Highly structured stochastic system. New York: Oxford University Press, 2003:70-82.
4. van der Laan MJ, Petersen ML. Direct effect models. Int J Biostat 2008;4:23.
5. Hafeman DM, VanderWeele TJ. Alternative assumptions for the identification of direct and indirect effects. Epidemiology 2011;22:753-64.
6. Shpitser I, VanderWeele TJ. A complete graphical criterion for the adjustment formula in mediation analysis. Int J Biostat 2011;7:16.
7. Cai Z, Kuroki M, Pearl J, Tian J. Bounds on direct effects in the presence of confounded intermediate variables. Biometrics 2008;64:695-701.
8. Sjölander A. Bounds on natural direct effects in the presence of confounded intermediate variables. Stat Med 2009;28:558-71.
9. Kaufman S, Kaufman JS, MacLehose RF. Analytic bounds on causal risk differences in directed acyclic graphs involving three observed binary variables. J Stat Plann Inference 2009;139:3473-87.
10. Chiba Y. Bounds on controlled direct effects under monotonic assumptions about mediators and confounders. Biom J 2010;52:628-37.
11. VanderWeele TJ. Controlled direct and mediated effects: definition, identification and bounds. Scand J Stat 2011;38: 551-63.
12. Pearl J. Causal diagrams for empirical research. Biometrika 1995;82:669-88.
13. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology 1999;10:37-48.
14. Cole SR, Hernán MA. Constructing inverse probability weights for marginal structural models. Am J Epidemiol 2008;168:656-64.
15. VanderWeele TJ. Concerning the consistency assumption in causal inference. Epidemiology 2009;20:880-3.
16. Rubin DB. Comment on: Neyman (1923) and causal inference in experiments and observational studies. Stat Sci 1990;5:472-80.
17. Manski CF, Pepper JV. Monotone instrumental variables: with an application to the returns to schooling. Econometrica 2000;68:997-1010.
18. Chiba Y. Causal inference in randomized trials with noncompliance. In: Smigórski K, editor. Health management - different approaches and solutions. Rijeka: Intech, 2011:315-36.
19. The Lipid Research Clinics Coronary Primary Prevention Trial Results I. Reduction in incidence of coronary heart disease. J Am Med Assoc 1984;251:351-64.
20. Freedman LS, Graubard BI, Schatzkin A. Statistical validation of intermediate endpoints for chronic diseases. Stat Med 1992;11:167-78.
21. Heckman JJ, Vytlacil EJ. Instrumental variables, selection models, and tight bounds on the average treatment effect. In: Lechner M, Preiffer F, editors. Econometric evaluation of labour market policies. Heidelberg: Physica-Verlag, 2001:1-15.
22. Esary JD, Proschan F, Walkup DW. Association of random variables, with applications. Ann Math Stat 1967;38:1466-74.