IDEAS home Printed from

KITCHENSINK: Stata module to return the model with the highest number of statistically significant predictors


  • Francisco (Paco) Perales

    () (University of Queensland)


The command kitchensink promotes bad practice amongst the scientific community by returning the regression model with the highest number of statistically significant regressors using the outcome variable specified in depvar and a combination of the explanatory variables specified in indepvars. More 'serious' use of kitchensink can be made by specifying the option aic, which gives the best fitting possible model as denoted by Akaike's information criteria. Note that kitchensink requires Nicholas Cox's tuples routine to be installed and allows for a maximum of 10 explanatory variables.

Suggested Citation

  • Francisco (Paco) Perales, 2013. "KITCHENSINK: Stata module to return the model with the highest number of statistically significant predictors," Statistical Software Components S457643, Boston College Department of Economics.
  • Handle: RePEc:boc:bocode:s457643
    Note: This module should be installed from within Stata by typing "ssc install kitchensink". Windows users should not attempt to download these files with a web browser.

    Download full text from publisher

    File URL:
    File Function: program code
    Download Restriction: no

    File URL:
    File Function: help file
    Download Restriction: no

    More about this item


    data mining; AIC;


    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:bocode:s457643. 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.