IDEAS home Printed from https://ideas.repec.org/a/oup/biomet/v111y2024i2p537-550..html
   My bibliography  Save this article

Promises of parallel outcomes

Author

Listed:
  • Ying Zhou
  • Dingke Tang
  • Dehan Kong
  • Linbo Wang

Abstract

SummaryA key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we introduce a novel approach for causal inference that leverages information in multiple outcomes to deal with unmeasured confounding. An important assumption in our approach is conditional independence among multiple outcomes. In contrast to existing proposals in the literature, the roles of multiple outcomes in the conditional independence assumption are symmetric; hence, the name parallel outcomes. We show nonparametric identifiability with at least three parallel outcomes and provide parametric estimation tools under a set of linear structural equation models. Our proposal is evaluated through a set of synthetic and real data analyses.

Suggested Citation

  • Ying Zhou & Dingke Tang & Dehan Kong & Linbo Wang, 2024. "Promises of parallel outcomes," Biometrika, Biometrika Trust, vol. 111(2), pages 537-550.
  • Handle: RePEc:oup:biomet:v:111:y:2024:i:2:p:537-550.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/biomet/asae008
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:oup:biomet:v:111:y:2024:i:2:p:537-550.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/biomet .

    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.