Missing Data Handling

Authors

  • Dipalika Das , Maya Nayak, Subhendu Kumar Pani Author

DOI:

https://doi.org/10.48047/wgm6yb83

Abstract

Over the most recent few years, both the rate at which digital data is being produced and the rate at which computational power is being developed have accelerated dramatically. These enable the extraction of distinctive insights from enormous databases, commonly called "big data." Data analysts understand the challenges various industries face, including healthcare, banking, e-commerce, and finance.

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References

Chen Y - C, Pattern graphs: A graphical approach to non-monotone missing data, arXiv. 2004.00744, v2, 2020.

Lin W-C, Tsai C-F. Missing value imputation: A review and analysis of the literature (2006 – 2017). Artificial Intelligence Review. 2020; Vol. 53, Issue 2, 1487 – 1509.

Rubin, D. B., & Little, R. J. A. (2019). *Statistical Analysis with Missing Data* (3rd ed.). Wiley.

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Published

2025-02-03

Issue

Vol. 54 No. 3 (2025): Year 2025, Volume 54, Issue 3

Section

Articles

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How to Cite

Missing Data Handling (Dipalika Das , Maya Nayak, Subhendu Kumar Pani , Trans.). (2025). Cuestiones De Fisioterapia, 54(3), 2913-2925. https://doi.org/10.48047/wgm6yb83