IDEAS home Printed from https://ideas.repec.org/p/rtr/wpaper/0167.html
   My bibliography  Save this paper

Object-oriented bayesian networks for modelling the respondent measurement error

Author

Listed:
  • Daniela Marella
  • Paola Vicard

    ()

Abstract

In this paper Object-Oriented Bayesian networks are proposed as a tool to model measurement errors in a categorical variable due to respondent. A mixed measurement error model is presented and an Object-Oriented Bayesian network implementing such a model is introduced. The insertion of evidence represented by the observed value and its propagation throughout the network yields for each unit the probability distribution of the true value given the observed. Two methods are used to predict the individual true value and their performance is evaluated via simulation.

Suggested Citation

  • Daniela Marella & Paola Vicard, 2012. "Object-oriented bayesian networks for modelling the respondent measurement error," Departmental Working Papers of Economics - University 'Roma Tre' 0167, Department of Economics - University Roma Tre.
  • Handle: RePEc:rtr:wpaper:0167
    as

    Download full text from publisher

    File URL: http://dipeco.uniroma3.it/public/WP%20167.pdf
    Download Restriction: no

    More about this item

    Keywords

    Bayesian networks; Measurement errors; Respondent Error.;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:rtr:wpaper:0167. 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: (Telephone for information). General contact details of provider: http://edirc.repec.org/data/dero3it.html .

    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.