Approximate confidence intervals for the difference in proportions for partially observed binary data. (March 2022)

• Record Type: Journal Article
• Authors: Das, Ujjwal; Basu, Ranojoy
• Is Part Of: Statistical methods in medical research. Volume 31:Number 3(2022)
• Page Start: 488
• Page End: 509
• Publication Date: 2022-03
• Subjects: Paired binary data -- missing at random -- difference of proportion -- interval estimator -- incomplete data -- EM algorithm; Medicine -- Research -- Statistical methods -- Periodicals; Research -- Periodicals; Review Literature -- Periodicals; Statistics -- methods -- Periodicals; Médecine -- Recherche -- Méthodes statistiques -- Périodiques; 610.727
• DOI: 10.1177/09622802211060528
• Languages: English
• ISSNs: 0962-2802

Abstract

We consider partially observed binary matched-pair data. We assume that the incomplete subjects are missing at random. Within this missing framework, we propose an EM-algorithm based approach to construct an interval estimator of the proportion difference incorporating all the subjects. In conjunction with our proposed method, we also present two improvements to the interval estimator through some correction factors. The performances of the three competing methods are then evaluated through extensive simulation. Recommendation for the method is given based on the ability to preserve type-I error for various sample sizes. Finally, the methods are illustrated in two real-world data sets. AnR -function is developed to implement the three proposed methods.