Affiliations: [a] Department of Clinical Sciences and Simmons Cancer Center, UT Southwestern Medical Center, Dallas, TX, USA | [b] Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, USA
Corresponding author: 5323 Harry Hines Blvd-E1.402, Dallas, TX 75390-8822, USA. E-mail: [email protected].
Abstract: We consider misclassified binary data with a validation substudy. For such data various methods have been developed for estimating the odds ratio. It is well-known that the maximum likelihood estimator (MLE) of the odds ratio is efficient but requires iterative algorithms to compute. In this article, we derive a closed-form formula for the MLE and its asymptotic standard error. We compute the closed-form MLE on a data set that has been analyzed by other methods, and the results are compared.
Keywords: Binary data, confidence interval, invariance property of MLE, maximum likelihood estimation, misclassification, odds ratio