IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v10y2014i1p15n3.html
   My bibliography  Save this article

The Effect of Error-in-Confounders on the Estimation of the Causal Parameter When Using Marginal Structural Models and Inverse Probability-of-Treatment Weights: A Simulation Study

Author

Listed:
  • Regier Michael D.

    (West Virginia University, Morgantown, WV, USA)

  • Moodie Erica E. M.
  • Platt Robert W.

    (McGill University, Montréal, QC, Canada)

Abstract

We performed an empirical study to evaluate the effect of mismeasured continuous confounders on the estimation of the causal parameter when using marginal structural models and inverse probability-of-treatment weighting. By executing an extensive simulation using 500 randomly generated parameter value combinations within a defined space, we observed the well-understood effects of attenuation and augmentation, and two unanticipated effects: null effects and sign reversals. We implemented a secondary empirical study to further investigate the sign reversal effect. We use the results of our study to identify conceptual similarities between the analytic and empirical results for multivariable linear and logistic regression, and our empirical results. Through this synthesis, we have been able to suggest feasible directions of research as well as outline the form of expected results.

Suggested Citation

  • Regier Michael D. & Moodie Erica E. M. & Platt Robert W., 2014. "The Effect of Error-in-Confounders on the Estimation of the Causal Parameter When Using Marginal Structural Models and Inverse Probability-of-Treatment Weights: A Simulation Study," The International Journal of Biostatistics, De Gruyter, vol. 10(1), pages 1-15, May.
    • Handle: RePEc:bpj:ijbist:v:10:y:2014:i:1:p:15:n:3
    DOI: 10.1515/ijb-2012-0039
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/ijb-2012-0039
    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-2012-0039?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. Erica Moodie & D. Stephens, 2011. "Marginal Structural Models: unbiased estimation for longitudinal studies," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 56(1), pages 117-119, February.
    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. Di Shu & Grace Y. Yi, 2018. "Estimation of Causal Effect Measures in the Presence of Measurement Error in Confounders," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(1), pages 233-254, April.

    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. Regier Michael D. & Moodie Erica E. M., 2016. "The Orthogonally Partitioned EM Algorithm: Extending the EM Algorithm for Algorithmic Stability and Bias Correction Due to Imperfect Data," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 65-77, May.

    More about this item

    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:10:y:2014:i:1:p:15:n:3. 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.degruyter.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.