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

Vishwajeet Singh, Alok Kumar Dwivedi, Sada Nand Dwivedi and Deo Svs
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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
Deo Svs: Department of Surgical Oncology, All India Institute of Medical Sciences, India

Biostatistics and Biometrics Open Access Journal, 2018, vol. 8, issue 4, 84-90

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.

Keywords: Biometrics Open Access Journal; Biostatistics and Biometrics; Biostatistics and Biometrics Open Access Journal; Open Access Journals; biometrics journal; biometrics articles; biometrics journal reference; biometrics journal impact factor; biometrics and biostatistics journal impact factor; journal of biometrics; open access juniper publishers; juniper publishers reivew (search for similar items in EconPapers)
Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:adp:jbboaj:v:8:y:2018:i:4:p:84-90

DOI: 10.19080/BBOAJ.2018.08.555745

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