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Exact correction factor for estimating the OR in the presence of sparse data with a zero cell in 2 × 2 tables

Author

Listed:
  • Babu Malavika

    (Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India)

  • Mani Thenmozhi

    (Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India)

  • Sappani Marimuthu

    (Department of Biostatistics, Christian Medical College, Vellore, Tamil Nadu, India)

  • George Sebastian

    (Department of Statistical Sciences, Kannur University, Kannur, Kerala, India)

  • Bangdiwala Shrikant I.

    (Department of Health Research Methods, Evidence and Impact, McMaster University Faculty of Health Sciences, Hamilton, ON, Canada)

  • Jeyaseelan Lakshmanan

    (College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates)

Abstract

In case-control studies, odds ratios (OR) are calculated from 2 × 2 tables and in some instances, we observe small cell counts or zero counts in one of the cells. The corrections to calculate the ORs in the presence of empty cells are available in literature. Some of these include Yates continuity correction and Agresti and Coull correction. However, the available methods provided different corrections and the situations where each could be applied are not very apparent. Therefore, the current research proposes an iterative algorithm of estimating an exact (optimum) correction factor for the respective sample size. This was evaluated by simulating data with varying proportions and sample sizes. The estimated correction factor was considered after obtaining the bias, standard error of odds ratio, root mean square error and the coverage probability. Also, we have presented a linear function to identify the exact correction factor using sample size and proportion.

Suggested Citation

  • Babu Malavika & Mani Thenmozhi & Sappani Marimuthu & George Sebastian & Bangdiwala Shrikant I. & Jeyaseelan Lakshmanan, 2024. "Exact correction factor for estimating the OR in the presence of sparse data with a zero cell in 2 × 2 tables," The International Journal of Biostatistics, De Gruyter, vol. 20(1), pages 229-243.
    • Handle: RePEc:bpj:ijbist:v:20:y:2024:i:1:p:229-243:n:1005
    DOI: 10.1515/ijb-2022-0040
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