IDEAS home Printed from
   My bibliography  Save this article

Adaptive Centering with Random Effects: An Alternative to the Fixed Effects Model for Studying Time-Varying Treatments in School Settings


  • Stephen W. Raudenbush

    () (Department of Sociology, University of Chicago)


Fixed effects models are often useful in longitudinal studies when the goal is to assess the impact of teacher or school characteristics on student learning. In this article, I introduce an alternative procedure: adaptive centering with random effects. I show that this procedure can replicate the fixed effects analysis while offering several comparative advantages: the incorporation into standard errors of multiple levels of clustering; the modeling of heterogeneity of treatment effects; the estimation of effects of treatments at multiple levels; and computational simplicity. After illustrating these ideas in a simple setting, the article formulates a general linear model with adaptive centering and random effects and derives efficient estimates and standard errors. The results apply to studies that have an arbitrary number of nested and cross-classified factors such as time, students, classrooms, schools, districts, or states. © 2009 American Education Finance Association

Suggested Citation

  • Stephen W. Raudenbush, 2009. "Adaptive Centering with Random Effects: An Alternative to the Fixed Effects Model for Studying Time-Varying Treatments in School Settings," Education Finance and Policy, MIT Press, vol. 4(4), pages 468-491, October.
  • Handle: RePEc:tpr:edfpol:v:4:y:2009:i:4:p:468-491

    Download full text from publisher

    File URL:
    Download Restriction: Access to PDF is restricted to subscribers.

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


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

    Cited by:

    1. Cassandra M. Guarino & Mark D. Reckase & Jeffrey M. Woolrdige, 2014. "Can Value-Added Measures of Teacher Performance Be Trusted?," Education Finance and Policy, MIT Press, vol. 10(1), pages 117-156, November.
    2. Jung, Sang-Uk & Zhu, John & Gruca, Thomas S., 2016. "A meta-analysis of correlations between market share and other brand performance metrics in FMCG markets," Journal of Business Research, Elsevier, vol. 69(12), pages 5901-5908.

    More about this item


    fixed effects models; adaptive centering; time-varying treatments;

    JEL classification:

    • I20 - Health, Education, and Welfare - - Education - - - General
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education


    Access and download statistics


    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:tpr:edfpol:v:4:y:2009:i:4:p:468-491. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Kristin Waites). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.