IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v50y2021i2p491-530.html
   My bibliography  Save this article

Diagnosing Multicollinearity in Exponential Random Graph Models

Author

Listed:
  • Scott W. Duxbury

Abstract

Exponential random graph models (ERGM) have been widely applied in the social sciences in the past 10 years. However, diagnostics for ERGM have lagged behind their use. Collinearity-type problems can emerge without detection when fitting ERGM, yielding inconsistent model estimates and problematizing inference from parameters. This article provides a method to detect multicollinearity in ERGM. It outlines the problem and provides a method to calculate the variance inflation factor (VIF) from ERGM parameters. It then evaluates the method with a Monte Carlo simulation, fitting 216,000 ERGMs and calculating the VIFs for each model. The distribution of VIFs is analyzed using multilevel regression to determine what network characteristics lend themselves to collinearity-type problems. The relationship between VIFs and unstable standard errors (a standard sign of collinearity) is also examined. The method is shown to effectively detect multicollinearity, and guidelines for interpretation are discussed.

Suggested Citation

  • Scott W. Duxbury, 2021. "Diagnosing Multicollinearity in Exponential Random Graph Models," Sociological Methods & Research, , vol. 50(2), pages 491-530, May.
    • Handle: RePEc:sae:somere:v:50:y:2021:i:2:p:491-530
    DOI: 10.1177/0049124118782543
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124118782543
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124118782543?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
    ---><---

    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:somere:v:50:y:2021:i:2:p:491-530. 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.