IDEAS home Printed from
   My bibliography  Save this paper

User-written Stata program: agrm


  • Alejandro Ecker

    (University of Mannheim)


In the context of his research on perceptual agreement, Cees van der Eijk (2001, Quality & Quantity: 35, 325–341) indicates that empirical measures that resort to the standard deviation of the response distribution capture not only consensus but also skewedness. Thus they are inappropriate measures of agreement. His alternative measure of agreement, A, circumvents this problem and yields unbiased figures for all kinds of ordered rating scales. It first decomposes the frequency distribution into constituent layers, that is, row vectors for which consensus can be unambiguously defined. It then computes the weighted average degree of agreement. Given the lack of a corresponding ado-file, the user-written agrm command allows you to directly calculate van der Eijk’s index of agreement, A, in Stata. Aside from a broad range of basic programming features such as low-level parsing and specifying additional program options, argm also entails more advanced techniques such as handling empty categories and handling numerical missing values. Moreover, it highlights the potential of nested loops and local macros in the context of multiple permutations. Finally, the agrm command is especially suited for showing how Stata’s matrix language, Mata, provides a powerful environment for handling vectors and matrices.

Suggested Citation

  • Alejandro Ecker, 2010. "User-written Stata program: agrm," German Stata Users' Group Meetings 2010 07, Stata Users Group.
  • Handle: RePEc:boc:dsug10:07

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Blundell, Richard & Griffith, Rachel & Windmeijer, Frank, 2002. "Individual effects and dynamics in count data models," Journal of Econometrics, Elsevier, vol. 108(1), pages 113-131, May.
    Full references (including those not matched with items on IDEAS)

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    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:boc:dsug10:07. 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: (Christopher F Baum). 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.