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Inference for the treatment effects in two sample problems with right-censored and length-biased data
Institution:1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China;2. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, China;1. 231 W. Hancock St, Campus Box 17, Department of Mathematics, Georgia College & State University, Milledgeville, GA 31061, United States;2. 221 Parker Hall, Department of Mathematics and Statistics, Auburn University, Auburn, Al 36849, United States;1. Department of Mathematics and Statistics, Concordia University, Montréal, QC H3G 1M8, Canada;2. Department of Mathematical Sciences, Central Connecticut State University, 1615 Stanley Street, New Britain, CT 06050, USA;1. Department of Civil Engineering, Faculty of Engineering, Suleyman Demirel University, Isparta, Turkey;2. Department of Civil Engineering, Faculty of Engineering and Architecture of Istanbul Gelisim University, Istanbul, Turkey
Abstract:In the study of comparing treatment effects, the data structures of two samples may be different. In this paper, we develop a unified semiparametric estimating equation approach to estimate various types of treatment effects with right-censored and length-biased data based on a semiparametric two-sample model. The large sample properties of the proposed estimators are derived and numerical studies are conducted to illustrate the proposed methods.
Keywords:Estimating equation  Length bias  Semiparametric model  Treatment effect
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