IDEAS home Printed from https://ideas.repec.org/a/sae/jedbes/v29y2004i3p343-367.html
   My bibliography  Save this article

Teaching Statistical Inference for Causal Effects in Experiments and Observational Studies

Author

Listed:
  • Donald B. Rubin

Abstract

Inference for causal effects is a critical activity in many branches of science and public policy. The field of statistics is the one field most suited to address such problems, whether from designed experiments or observational studies. Consequently, it is arguably essential that departments of statistics teach courses in causal inference to both graduate and undergraduate students. This article discusses an outline of such courses based on repeated experience over more than a decade.

Suggested Citation

  • Donald B. Rubin, 2004. "Teaching Statistical Inference for Causal Effects in Experiments and Observational Studies," Journal of Educational and Behavioral Statistics, , vol. 29(3), pages 343-367, September.
  • Handle: RePEc:sae:jedbes:v:29:y:2004:i:3:p:343-367
    DOI: 10.3102/10769986029003343
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.3102/10769986029003343
    Download Restriction: no

    File URL: https://libkey.io/10.3102/10769986029003343?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
    ---><---

    Citations

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


    Cited by:

    1. Yu-Jen Cheng & Mei-Cheng Wang, 2015. "Causal estimation using semiparametric transformation models under prevalent sampling," Biometrics, The International Biometric Society, vol. 71(2), pages 302-312, June.
    2. Gargani, John, 2017. "The leap from ROI to SROI: Farther than expected?," Evaluation and Program Planning, Elsevier, vol. 64(C), pages 116-126.
    3. Hohenleitner, Ingrid & Hillmann, Katja, 2019. "Impact of welfare sanctions on employment and benefit receipt: Considering top-up benefits and indirect sanctions," HWWI Research Papers 189, Hamburg Institute of International Economics (HWWI).
    4. Rüdiger Mutz & Hans-Dieter Daniel, 2012. "The generalized propensity score methodology for estimating unbiased journal impact factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 377-390, August.
    5. Armstrong, Christopher S. & Kepler, John D., 2018. "Theory, research design assumptions, and causal inferences," Journal of Accounting and Economics, Elsevier, vol. 66(2), pages 366-373.
    6. Tenglong Li & Kenneth A. Frank, 2019. "On the probability of a causal inference is robust for internal validity," Papers 1906.08726, arXiv.org.
    7. Eunah Jung & Heeyeun Yoon, 2018. "Is Flood Risk Capitalized into Real Estate Market Value? A Mahalanobis-Metric Matching Approach to the Housing Market in Gyeonggi, South Korea," Sustainability, MDPI, vol. 10(11), pages 1-17, November.

    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:sae:jedbes:v:29:y:2004:i:3:p:343-367. 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: SAGE Publications (email available below). General contact details of provider: .

    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.