Skip Navigation

Biometrika 1999 86(1):1-13; doi:10.1093/biomet/86.1.1
© 1999 by Biometrika Trust
This Article
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Chen, H.
Right arrow Articles by Little, R
Right arrow Search for Related Content
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

A test of missing completely at random for generalised estimating equations with missing data

HY ChenA and R LittleA2

A Division of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL 60680, USA hychen@uic.edu A2 Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA rlittle@umich.edu

We consider inference from generalised estimating equations when data are incomplete. A test for missing completely at random is proposed to help decide whether or not we should adjust estimating equations to correct the possible bias introduced by a missing-data mechanism that is not missing completely at random. Likelihood ratio tests have been introduced to test the missing completely at random hypothesis (Fuchs, 1982; Little, 1988). For the estimating equation setting, following the basic idea of Little (1988), we propose a Wald-type test based on an information decomposition and recombination procedure, which also provides an alternative method for estimating parameters. One application of the test is to assess the adequacy of the marginal generalised estimating equation for longitudinal data with missing values. Simulations are done to evaluate its performance.

Keywords:Drop-out; Incomplete data; Longitudinal data; Missing-data mechanism.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 Stat Methods Med ResHome page
R. F Potthoff, G. E Tudor, K. S Pieper, and V. Hasselblad
Can one assess whether missing data are missing at random in medical studies?
Statistical Methods in Medical Research, June 1, 2006; 15(3): 213 - 234.
[Abstract] [PDF]

Home page
 Arch Pediatr Adolesc MedHome page
P. Lozano, J. A. Finkelstein, V. J. Carey, E. H. Wagner, T. S. Inui, A. L. Fuhlbrigge, S. B. Soumerai, S. D. Sullivan, S. T. Weiss, and K. B. Weiss
A Multisite Randomized Trial of the Effects of Physician Education and Organizational Change in Chronic-Asthma Care: Health Outcomes of the Pediatric Asthma Care Patient Outcomes Research Team II Study
Arch Pediatr Adolesc Med, September 1, 2004; 158(9): 875 - 883.
[Abstract] [Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.