IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v18y2018i2p447-460.html
   My bibliography  Save this article

Inference for clustered data

Author

Listed:
  • Chang Hyung Lee

    (University of California, Santa Barbara)

  • Douglas G. Steigerwald

    (University of California, Santa Barbara)

Abstract

In this article, we introduce clusteff, a community-contributed com- mand for checking the severity of cluster heterogeneity in cluster–robust analyses. Cluster heterogeneity can cause a size distortion leading to underrejection of the null hypothesis. Carter, Schnepel, and Steigerwald (2017, Review of Economics and Statistics 99: 698–709) develop the effective number of clusters to reflect a reduction in the degrees of freedom, thereby mirroring the distortion caused by assuming homogeneous clusters. clusteff generates the effective number of clus- ters. We provide a decision tree for cluster–robust analysis, demonstrate the use of clusteff, and recommend methods to minimize the size distortion.

Suggested Citation

  • Chang Hyung Lee & Douglas G. Steigerwald, 2018. "Inference for clustered data," Stata Journal, StataCorp LP, vol. 18(2), pages 447-460, June.
    • Handle: RePEc:tsj:stataj:v:18:y:2018:i:2:p:447-460
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/article.html?article=st0531
    File Function: link to article purchase
    Download Restriction: no
    File URL: http://www.stata-journal.com/software/sj18-2/st0531/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Mikola, Derek & Webb, Matthew D., 2023. "Finish it and it is free: An evaluation of college graduation subsidies," Economics of Education Review, Elsevier, vol. 93(C).
    2. James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2023. "Leverage, influence, and the jackknife in clustered regression models: Reliable inference using summclust," Stata Journal, StataCorp LP, vol. 23(4), pages 942-982, December.
    3. Carpenter, Christopher S. & Gonzales, Gilbert & McKay, Tara & Sansone, Dario, 2020. "Effects of the Affordable Care Act Dependent Coverage Mandate on Health Insurance Coverage for Individuals in Same-Sex Couples," IZA Discussion Papers 13119, Institute of Labor Economics (IZA).
    4. MacKinnon, James G. & Nielsen, Morten Ørregaard & Webb, Matthew D., 2023. "Cluster-robust inference: A guide to empirical practice," Journal of Econometrics, Elsevier, vol. 232(2), pages 272-299.
    5. David Roodman & James G. MacKinnon & Morten Ørregaard Nielsen & Matthew D. Webb, 2019. "Fast and wild: Bootstrap inference in Stata using boottest," Stata Journal, StataCorp LP, vol. 19(1), pages 4-60, March.
    6. Harris, Lena, 2024. "Farmer response to policy induced water reductions: Evidence from the Colorado River," Journal of Environmental Economics and Management, Elsevier, vol. 125(C).
    7. James G. MacKinnon & Matthew D. Webb, 2020. "When and How to Deal with Clustered Errors in Regression Models," Working Paper 1421, Economics Department, Queen's University.
    8. Gawain Heckley & Martin Nordin & Ulf‐G. Gerdtham, 2022. "The health returns of attending university for the marginally eligible student," Health Economics, John Wiley & Sons, Ltd., vol. 31(5), pages 877-903, May.
    9. Deb, Partha & Gangaram, Anjelica & Khajavi, Hoda Nouri, 2021. "The impact of the State Innovation Models Initiative on population health," Economics & Human Biology, Elsevier, vol. 42(C).
    10. Honjo, Yuji & Ono, Arito & Tsuruta, Daisuke, 2024. "The effect of physical collateral and personal guarantees on business startups," Journal of Economics and Business, Elsevier, vol. 130(C).
    11. Jeremy Edwards, 2021. "Can Institutional Transplants Work? A Reassessment of the Evidence from Nineteenth-Century Prussia," CESifo Working Paper Series 9333, CESifo.
    12. Chang Hyung Lee, 2020. "Minimum Wage Policy and Community College Enrollment Patterns," ILR Review, Cornell University, ILR School, vol. 73(1), pages 178-210, January.
    13. Child, Travers Barclay & Massoud, Nadia & Schabus, Mario & Zhou, Yifan, 2021. "Surprise election for Trump connections," Journal of Financial Economics, Elsevier, vol. 140(2), pages 676-697.

    More about this item

    Keywords

    clusteff; cluster heterogeneity;

    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:tsj:stataj:v:18:y:2018:i:2:p:447-460. 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: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.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.