IDEAS home Printed from https://ideas.repec.org/a/bpj/ijbist/v6y2010i2n13.html
   My bibliography  Save this article

Accuracy of Conventional and Marginal Structural Cox Model Estimators: A Simulation Study

Author

Listed:
  • Xiao Yongling

    (McGill University)

  • Abrahamowicz Michal

    (McGill University & Montreal General Hospital)

  • Moodie Erica E. M.

    (McGill University)

Abstract

Marginal structural models (MSM) provide a powerful tool to control for confounding by a time-dependent covariate without inappropriately adjusting for its role as a variable affected by treatment (Hernán et al., 2000). In this paper, we demonstrate that it is possible to fit a marginal structural Cox model directly, rather than the typical approach of using pooled logistic regression, using the weighted Cox proportional hazards function that has been implemented in standard software. To evaluate the performance of the marginal structural Cox model directly via inverse probability of treatment weighting, we conducted several simulation studies based on two data-generating models: one which replicates the simulations of Young et al. (2009) and an additional, more clinically plausible approach which mimics survival data with time-dependent confounders and time-varying treatment. Using the simulations, we illustrate the limitations of the conventional time-dependent Cox model and the MSM fitted via pooled logistic regression. Furthermore, we propose two novel normalized weights with the goal of reducing the MSM estimators' variability. The performance of the normalized weights is evaluated alongside the usual unstabilized and stabilized weights.

Suggested Citation

  • Xiao Yongling & Abrahamowicz Michal & Moodie Erica E. M., 2010. "Accuracy of Conventional and Marginal Structural Cox Model Estimators: A Simulation Study," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-30, March.
    • Handle: RePEc:bpj:ijbist:v:6:y:2010:i:2:n:13
    DOI: 10.2202/1557-4679.1208
    as

    Download full text from publisher

    File URL: https://doi.org/10.2202/1557-4679.1208
    Download Restriction: For access to full text, subscription to the journal or payment for the individual article is required.
    File URL: https://libkey.io/10.2202/1557-4679.1208?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.

    Citations

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


    Cited by:

    1. Mireille E. Schnitzer & Erica E.M. Moodie & Mark J. van der Laan & Robert W. Platt & Marina B. Klein, 2014. "Modeling the impact of hepatitis C viral clearance on end-stage liver disease in an HIV co-infected cohort with targeted maximum likelihood estimation," Biometrics, The International Biometric Society, vol. 70(1), pages 144-152, March.
    2. 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.
    3. Gruber, Susan & Laan, Mark van der, 2012. "tmle: An R Package for Targeted Maximum Likelihood Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i13).

    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:6:y:2010:i:2:n:13. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.