Inference for Kappas for Longitudinal Study Data: Applications to Sexual Health Research

• Activity Number: 139
• Type: Contributed
• Date/Time: Monday, August 2, 2010 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Epidemiology
• Author(s): Yan Ma*+ and Wan Tang and Changyong Feng and Xin M. Tu
• Companies: Hospital for Special Surgery, Weill Medical College of Cornell University and University of Rochester and University of Rochester Medical Center and University of Rochester
• Keywords: Inverse probability weighting ; Missing data ; Monotone missing data pattern ; Sexual health ; U-statistics

Abstract

Analysis of instrument reliability and rater agreement is used in a wide range of behavioral, and medical research to assess psychometric properties of instruments,and accuracy of proxy outcomes.For categorical outcomes, Cohen's kappa is the most widely used index of agreement and reliability. In modern-day applications, data are often clustered,making inference difficult to perform using existing methods.In addition, as longitudinal study designs become increasingly popular, missing data has become a serious issue, and the lack of methods to systematically address this problem has hampered the progress of research in the aforementioned fields.In this paper, we develop a novel approach based on a new class of kappa estimates to tackle the complexities involved in addressing missing data and other related issues arising from a general multi-rater and longitudinal setting.