IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v9y2013i2p235-249n2.html

Alternative Monotonicity Assumptions for Improving Bounds on Natural Direct Effects

Author

Listed:
  • Chiba Yasutaka

    (Division of Biostatistics, Clinical Research Center, Kinki University School of Medicine, Osaka, Japan)

  • Taguri Masataka

    (Department of Biostatistics and Epidemiology, Graduate School of Medicine, Yokohama City University, Yokohama, Japan)

Abstract

Estimating the direct effect of a treatment on an outcome is often the focus of epidemiological and clinical research, when the treatment has more than one specified pathway to the defined outcome. Even if the total effect is unconfounded, the direct effect is not identified when unmeasured variables affect the intermediate and outcome variables. Therefore, bounds on direct effects have been presented via linear programming under two common definitions of direct effects: controlled and natural. Here, we propose bounds on natural direct effects without using linear programming, because such bounds on controlled direct effects have already been proposed. To derive narrow bounds, we introduce two monotonicity assumptions that are weaker than those in previous studies and another monotonicity assumption. Furthermore, we do not assume that an outcome variable is binary, whereas previous studies have made that assumption. An additional advantage of our bounds is that the bounding formulas are extremely simple. The proposed bounds are illustrated using a randomized trial for coronary heart disease.

Suggested Citation

  • Chiba Yasutaka & Taguri Masataka, 2013. "Alternative Monotonicity Assumptions for Improving Bounds on Natural Direct Effects," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 235-249, July.
  • Handle: RePEc:bpj:ijbist:v:9:y:2013:i:2:p:235-249:n:2
    DOI: 10.1515/ijb-2012-0022
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/ijb-2012-0022
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.

    File URL: https://libkey.io/10.1515/ijb-2012-0022?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Zhihong Cai & Manabu Kuroki & Judea Pearl & Jin Tian, 2008. "Bounds on Direct Effects in the Presence of Confounded Intermediate Variables," Biometrics, The International Biometric Society, vol. 64(3), pages 695-701, September.
    2. Charles F. Manski & John V. Pepper, 2000. "Monotone Instrumental Variables, with an Application to the Returns to Schooling," Econometrica, Econometric Society, vol. 68(4), pages 997-1012, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lixiong Li & Désiré Kédagni & Ismaël Mourifié, 2024. "Discordant relaxations of misspecified models," Quantitative Economics, Econometric Society, vol. 15(2), pages 331-379, May.
    2. Ting Ye & Luke Keele & Raiden Hasegawa & Dylan S. Small, 2020. "A Negative Correlation Strategy for Bracketing in Difference-in-Differences," Papers 2006.02423, arXiv.org, revised Jun 2022.
    3. Denis Chetverikov & Daniel Wilhelm, 2017. "Nonparametric instrumental variable estimation under monotonicity," CeMMAP working papers 14/17, Institute for Fiscal Studies.
    4. Jiang Zhichao & Chiba Yasutaka & VanderWeele Tyler J., 2014. "Monotone Confounding, Monotone Treatment Selection and Monotone Treatment Response," Journal of Causal Inference, De Gruyter, vol. 2(1), pages 1-12, March.
    5. C, Loran & Eckbo, Espen & Lu, Ching-Chih, 2014. "Does Executive Compensation Reflect Default Risk?," UiS Working Papers in Economics and Finance 2014/11, University of Stavanger.
    6. repec:isu:genstf:201201010800003618 is not listed on IDEAS
    7. Ismaël Mourifié & Marc Henry & Romuald Méango, 2020. "Sharp Bounds and Testability of a Roy Model of STEM Major Choices," Journal of Political Economy, University of Chicago Press, vol. 128(8), pages 3220-3283.
    8. Menzel, Konrad, 2014. "Consistent estimation with many moment inequalities," Journal of Econometrics, Elsevier, vol. 182(2), pages 329-350.
    9. Nguezet, Paul Martin Dontsop & Diagne, Aliou & Okoruwa, Victor Olusegun & Ojehomon, Vivian, 2011. "Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(3), pages 1-25.
    10. Belzil, Christian & Hansen, Jorgen, 2007. "A structural analysis of the correlated random coefficient wage regression model," Journal of Econometrics, Elsevier, vol. 140(2), pages 827-848, October.
    11. Brock, William A. & Durlauf, Steven N., 2007. "Identification of binary choice models with social interactions," Journal of Econometrics, Elsevier, vol. 140(1), pages 52-75, September.
    12. Liu, Ding & Millimet, Daniel L., 2020. "Bounding the Joint Distribution of Disability and Employment with Contaminated Data," IZA Discussion Papers 13020, IZA Network @ LISER.
    13. Li, Hao & Millimet, Daniel L. & Roychowdhury, Punarjit, 2019. "Measuring Economic Mobility in India Using Noisy Data: A Partial Identification Approach," IZA Discussion Papers 12505, IZA Network @ LISER.
    14. Charles F. Manski, 2017. "Improving Clinical Guidelines and Decisions under Uncertainty," NBER Working Papers 23915, National Bureau of Economic Research, Inc.
    15. Molinari, Francesca, 2010. "Missing Treatments," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(1), pages 82-95.
    16. Ruth Miquel, 2002. "Identification of Dynamic Treatment Effects by Instrumental Variables," University of St. Gallen Department of Economics working paper series 2002 2002-11, Department of Economics, University of St. Gallen.
    17. Matthew A Masten & Alexandre Poirier, 2023. "Choosing exogeneity assumptions in potential outcome models," The Econometrics Journal, Royal Economic Society, vol. 26(3), pages 327-349.
    18. Lee, Sokbae & Song, Kyungchul & Whang, Yoon-Jae, 2018. "Testing For A General Class Of Functional Inequalities," Econometric Theory, Cambridge University Press, vol. 34(5), pages 1018-1064, October.
    19. Donald W. K. Andrews & Xiaoxia Shi, 2013. "Inference Based on Conditional Moment Inequalities," Econometrica, Econometric Society, vol. 81(2), pages 609-666, March.
    20. Santiago Acerenza & Otávio Bartalotti & Désiré Kédagni, 2023. "Testing identifying assumptions in bivariate probit models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(3), pages 407-422, April.
    21. Gu, Jiaying & Russell, Thomas M., 2023. "Partial identification in nonseparable binary response models with endogenous regressors," Journal of Econometrics, Elsevier, vol. 235(2), pages 528-562.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:ijbist:v:9:y:2013:i:2:p:235-249:n:2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyterbrill.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.