ERIC Number: EJ878840
Record Type: Journal
Publication Date: 2010-Mar
Abstractor: As Provided
Reference Count: 0
Modeling Concordance Correlation Coefficient for Longitudinal Study Data
Ma, Yan; Tang, Wan; Yu, Qin; Tu, X. M.
Psychometrika, v75 n1 p99-119 Mar 2010
Measures of agreement are used in a wide range of behavioral, biomedical, psychosocial, and health-care related research to assess reliability of diagnostic test, psychometric properties of instrument, fidelity of psychosocial intervention, and accuracy of proxy outcome. The concordance correlation coefficient (CCC) is a popular measure of agreement for continuous outcomes. 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 have 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 to tackle the complexities involved in addressing missing data and other related issues for performing CCC analysis within a longitudinal data setting. The approach is illustrated with both real and simulated data.
Descriptors: Diagnostic Tests, Correlation, Psychometrics, Intervention, Evaluation Methods, Longitudinal Studies, Data Analysis, Behavioral Science Research
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: email@example.com; Web site: http://www.springerlink.com
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Authoring Institution: N/A