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Challenges and Implications of Missing Data on the Validity of Inferences and Options for Choosing the Right Strategy in Handling Them

Received: 29 September 2017     Accepted: 17 October 2017     Published: 20 November 2017
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Abstract

Missing data in surveys and experimental research is a common occurrence which has serious implications on the validity of inferences. Advances in statistical procedures provides better and efficient methods of handling missing data yet many researches still handle incomplete data in ways that affects the results negatively. We review in detail the mechanisms that generates missingness, and the appropriate methods to account for the missing values to enable the researcher have adequate knowledge to make informed decision on the choice of method to account for missingness.

Published in International Journal of Statistical Distributions and Applications (Volume 3, Issue 4)
DOI 10.11648/j.ijsd.20170304.15
Page(s) 87-94
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Missing Data, Inference, Missingness Mechanisms, Ignorable, Non-Ignorable Missingness, Multiple Imputation

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Cite This Article
  • APA Style

    Nicholas Pindar Dibal, Ray Okafor, Hamadu Dallah. (2017). Challenges and Implications of Missing Data on the Validity of Inferences and Options for Choosing the Right Strategy in Handling Them. International Journal of Statistical Distributions and Applications, 3(4), 87-94. https://doi.org/10.11648/j.ijsd.20170304.15

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    ACS Style

    Nicholas Pindar Dibal; Ray Okafor; Hamadu Dallah. Challenges and Implications of Missing Data on the Validity of Inferences and Options for Choosing the Right Strategy in Handling Them. Int. J. Stat. Distrib. Appl. 2017, 3(4), 87-94. doi: 10.11648/j.ijsd.20170304.15

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    AMA Style

    Nicholas Pindar Dibal, Ray Okafor, Hamadu Dallah. Challenges and Implications of Missing Data on the Validity of Inferences and Options for Choosing the Right Strategy in Handling Them. Int J Stat Distrib Appl. 2017;3(4):87-94. doi: 10.11648/j.ijsd.20170304.15

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  • @article{10.11648/j.ijsd.20170304.15,
      author = {Nicholas Pindar Dibal and Ray Okafor and Hamadu Dallah},
      title = {Challenges and Implications of Missing Data on the Validity of Inferences and Options for Choosing the Right Strategy in Handling Them},
      journal = {International Journal of Statistical Distributions and Applications},
      volume = {3},
      number = {4},
      pages = {87-94},
      doi = {10.11648/j.ijsd.20170304.15},
      url = {https://doi.org/10.11648/j.ijsd.20170304.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsd.20170304.15},
      abstract = {Missing data in surveys and experimental research is a common occurrence which has serious implications on the validity of inferences. Advances in statistical procedures provides better and efficient methods of handling missing data yet many researches still handle incomplete data in ways that affects the results negatively. We review in detail the mechanisms that generates missingness, and the appropriate methods to account for the missing values to enable the researcher have adequate knowledge to make informed decision on the choice of method to account for missingness.},
     year = {2017}
    }
    

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Author Information
  • Department of Mathematical Sciences, University of Maiduguri, Maiduguri, Nigeria

  • Department of Mathematics, University of Lagos, Lagos, Nigeria

  • Department of Actuarial Science, University of Lagos, Lagos, Nigeria

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