IDEAS home Printed from https://ideas.repec.org/p/clb/wpaper/201015.html
   My bibliography  Save this paper

Missing-Values Adjustment For Mixed-Type Data

Author

Listed:
  • Agostino Tarsitano
  • Marianna Falcone

    (Dipartimento di Economia e Statistica, Università della Calabria)

Abstract

In this paper we propose a new method of single imputation, reconstruction, and estimation of non-reported, incorrect or excluded values both in the target and in the auxiliary variables where the first is on ratio or interval scale and the last are heterogeneous in measurement scale. Our technique is a variation of the popular nearest neighbor hot deck imputation (NNHDI) where "nearest" is defined in terms of a global distance obtained as a convex combination of the partial distance matrices computed for the various types of variables. In particular, we address the problem of proper weighting the partial distance matrices in order to reflect their significance, reliability and statistical adequacy. Performance of several weighting schemes is compared under a variety of settings in coordination with imputation of the least power mean. We have demonstrated, through analysis of simulated and actual data sets, the appropriateness of this approach. Our main contribution has been to show that mixed data may optimally be combined to allow accurate reconstruction of missing values in the target variable even in the absence of some data in the other fields of the record.

Suggested Citation

  • Agostino Tarsitano & Marianna Falcone, 2010. "Missing-Values Adjustment For Mixed-Type Data," Working Papers 201015, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    • Handle: RePEc:clb:wpaper:201015
    as

    Download full text from publisher

    File URL: http://www.hindawi.com/journals/jps/2011/290380/
    File Function: First version, 2010-08
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Nadia Solaro & Alessandro Barbiero & Giancarlo Manzi & Pier Alda Ferrari, 2017. "A sequential distance-based approach for imputing missing data: Forward Imputation," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 11(2), pages 395-414, June.
    2. Mr. Michael Weber & Ms. Michaela Denk, 2011. "Avoid Filling Swiss Cheese with Whipped Cream: Imputation Techniques and Evaluation Procedures for Cross-Country Time Series," IMF Working Papers 2011/151, International Monetary Fund.

    More about this item

    Keywords

    hot-deck imputation; nearest neighbor; general distance coefficient; least power mean;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • 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:clb:wpaper:201015. 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: Giovanni Dodero (email available below). General contact details of provider: https://edirc.repec.org/data/decalit.html .

    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.