IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v125y2017icp104-109.html
   My bibliography  Save this article

The directions of selection bias

Author

Listed:
  • Jiang, Zhichao
  • Ding, Peng

Abstract

We show that if the exposure and the outcome affect the selection indicator in the same direction and have non-positive interaction on the risk difference, risk ratio or odds ratio scale, the exposure-outcome odds ratio in the selected population is a lower bound for the true odds ratio.

Suggested Citation

  • Jiang, Zhichao & Ding, Peng, 2017. "The directions of selection bias," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 104-109.
    • Handle: RePEc:eee:stapro:v:125:y:2017:i:c:p:104-109
    DOI: 10.1016/j.spl.2017.01.022
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167715217300445
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.spl.2017.01.022?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Sander Greenland, 2005. "Multiple‐bias modelling for analysis of observational data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 168(2), pages 267-306, March.
    2. Peng Ding & Tyler J. Vanderweele, 2016. "Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding," Biometrika, Biometrika Trust, vol. 103(2), pages 483-490.
    3. P. Ding & T.J. Vanderweele & J. M. Robins, 2017. "Instrumental variables as bias amplifiers with general outcome and confounding," Biometrika, Biometrika Trust, vol. 104(2), pages 291-302.
    4. Tyler J. VanderWeele & James M. Robins, 2010. "Signed directed acyclic graphs for causal inference," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 72(1), pages 111-127, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Shahar Doron J. & Shahar Eyal, 2017. "A Theorem at the Core of Colliding Bias," The International Journal of Biostatistics, De Gruyter, vol. 13(1), pages 1-11, May.

    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. Leah Comment & Brent A. Coull & Corwin Zigler & Linda Valeri, 2022. "Bayesian data fusion: Probabilistic sensitivity analysis for unmeasured confounding using informative priors based on secondary data," Biometrics, The International Biometric Society, vol. 78(2), pages 730-741, June.
    2. Lawrence C. McCandless & Sylvia Richardson & Nicky Best, 2012. "Adjustment for Missing Confounders Using External Validation Data and Propensity Scores," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 107(497), pages 40-51, March.
    3. Douglas E. Schaubel & Guanghui Wei, 2011. "Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring," Biometrics, The International Biometric Society, vol. 67(1), pages 29-38, March.
    4. McCandless Lawrence C., 2012. "Meta-Analysis of Observational Studies with Unmeasured Confounders," The International Journal of Biostatistics, De Gruyter, vol. 8(2), pages 1-31, January.
    5. Maria Gheorghe & Susan Picavet & Monique Verschuren & Werner B. F. Brouwer & Pieter H. M. Baal, 2017. "Health losses at the end of life: a Bayesian mixed beta regression approach," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 180(3), pages 723-749, June.
    6. Rebecca M. Turner & David J. Spiegelhalter & Gordon C. S. Smith & Simon G. Thompson, 2009. "Bias modelling in evidence synthesis," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 21-47, January.
    7. Guido W. Imbens, 2020. "Potential Outcome and Directed Acyclic Graph Approaches to Causality: Relevance for Empirical Practice in Economics," Journal of Economic Literature, American Economic Association, vol. 58(4), pages 1129-1179, December.
    8. Qi Zhou & Yoo-Mi Chin & James D. Stamey & Joon Jin Song, 2020. "Bayesian sensitivity analysis to unmeasured confounding for misclassified data," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 104(4), pages 577-596, December.
    9. de Luna, Xavier & Lundin, Mathias, 2009. "Sensitivity analysis of the unconfoundedness assumption in observational studies," Working Paper Series 2009:12, IFAU - Institute for Evaluation of Labour Market and Education Policy.
    10. N. J. Welton & A. E. Ades & J. B. Carlin & D. G. Altman & J. A. C. Sterne, 2009. "Models for potentially biased evidence in meta‐analysis using empirically based priors," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(1), pages 119-136, January.
    11. P. Gustafson & L. C. McCandless & A. R. Levy & S. Richardson, 2010. "Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders," Biometrics, The International Biometric Society, vol. 66(4), pages 1129-1137, December.
    12. Sanjay Chaudhuri, 2014. "Qualitative inequalities for squared partial correlations of a Gaussian random vector," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(2), pages 345-367, April.
    13. D’Amour, Alexander & Ding, Peng & Feller, Avi & Lei, Lihua & Sekhon, Jasjeet, 2021. "Overlap in observational studies with high-dimensional covariates," Journal of Econometrics, Elsevier, vol. 221(2), pages 644-654.
    14. Desiree C Wilks & Stephen J Sharp & Ulf Ekelund & Simon G Thompson & Adrian P Mander & Rebecca M Turner & Susan A Jebb & Anna Karin Lindroos, 2011. "Objectively Measured Physical Activity and Fat Mass in Children: A Bias-Adjusted Meta-Analysis of Prospective Studies," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-8, February.
    15. Xavier de Luna & Mathias Lundin, 2014. "Sensitivity analysis of the unconfoundedness assumption with an application to an evaluation of college choice effects on earnings," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(8), pages 1767-1784, August.
    16. Muhammad Zia Hydari & Rahul Telang & William M. Marella, 2019. "Saving Patient Ryan—Can Advanced Electronic Medical Records Make Patient Care Safer?," Management Science, INFORMS, vol. 67(5), pages 2041-2059, May.
    17. Rebecca M Turner & Myfanwy Lloyd-Jones & Dilly O C Anumba & Gordon C S Smith & David J Spiegelhalter & Hazel Squires & John W Stevens & Michael J Sweeting & Stanislaw J Urbaniak & Robert Webster & Sim, 2012. "Routine Antenatal Anti-D Prophylaxis in Women Who Are Rh(D) Negative: Meta-Analyses Adjusted for Differences in Study Design and Quality," PLOS ONE, Public Library of Science, vol. 7(2), pages 1-10, February.
    18. Nuoo‐Ting Molitor & Nicky Best & Chris Jackson & Sylvia Richardson, 2009. "Using Bayesian graphical models to model biases in observational studies and to combine multiple sources of data: application to low birth weight and water disinfection by‐products," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 172(3), pages 615-637, June.
    19. Firat Bilgel, 2021. "Infant mortality in Turkey: Causes and effects in a regional context," Papers in Regional Science, Wiley Blackwell, vol. 100(2), pages 429-453, April.
    20. Laura L. F. Scott & George Maldonado, 2015. "Quantifying and Adjusting for Disease Misclassification Due to Loss to Follow-Up in Historical Cohort Mortality Studies," IJERPH, MDPI, vol. 12(10), pages 1-13, October.

    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:eee:stapro:v:125:y:2017:i:c:p:104-109. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.