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Comparative Appraisal of Estimated Odds Ratio and Risk Ratio Using Binary Regression Models Analysis of Nodal Involvement Among Oral-Cancer Patients

Author

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  • Vishwajeet Singh

    (Department of Biostatistics, All India Institute of Medical Sciences, India)

  • Alok Kumar Dwivedi

    (Department of Biostatistics, All India Institute of Medical Sciences, India)

  • Sada Nand Dwivedi

    (Division of Biostatistics & Epidemiology, Texas Tech University Health Sciences Center, USA)

  • SVS Deo

    (Department of Surgical Oncology, All India Institute of Medical Sciences, India)

Abstract

Predictive modeling for binary outcome in the form of logistic regression is very common in medical area. However, there is a substantial debate on the estimate of most appropriate association measures while analyzing binary outcomes. Odds ratio (OR) needs to be used in the case of case-control study only whereas prevalence ratio (PR) which is equivalent to relative risk (RR) should be appropriately used in the case of cross-sectional studies. Recently, Dwivedi et al. [1] proposed a modification in Diaz-Quijano method (BRR) to estimate RR along with appropriate 95% CI directly from logistic regression for a prevalent binary outcome.

Suggested Citation

  • Vishwajeet Singh & Alok Kumar Dwivedi & Sada Nand Dwivedi & SVS Deo, 2018. "Comparative Appraisal of Estimated Odds Ratio and Risk Ratio Using Binary Regression Models Analysis of Nodal Involvement Among Oral-Cancer Patients," Biostatistics and Biometrics Open Access Journal, Juniper Publishers Inc., vol. 8(4), pages 84-90, November.
    • Handle: RePEc:adp:jbboaj:v:8:y:2018:i:4:p:84-90
    DOI: 10.19080/BBOAJ.2018.08.555745
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    References listed on IDEAS

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    1. Alok Kumar Dwivedi & Indika Mallawaarachchi & Soyoung Lee & Patrick Tarwater, 2014. "Methods for estimating relative risk in studies of common binary outcomes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(3), pages 484-500, March.
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