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dc.contributor.authorJeyaseelan, Lakshmanan
dc.date.accessioned2023-10-18T07:21:24Z
dc.date.available2023-10-18T07:21:24Z
dc.date.issued2023
dc.identifier.other204-2023.79
dc.identifier.urihttps://repository.mbru.ac.ae/handle/1/1347
dc.description.abstractAbstract: 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.en_US
dc.language.isoenen_US
dc.subjectCorrection Factoren_US
dc.subjectCoverage Probabilityen_US
dc.subjectOdds Ratioen_US
dc.subjectRMSEen_US
dc.subjectSparsityen_US
dc.titleExact correction factor for estimating the OR in the presence of sparse data with a zero cell in 2 × 2 tablesen_US
dc.typeArticleen_US


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