Directly parameterized regression conditioning on being alive: analysis of longitudinal data truncated by deaths
National Alzheimer's Coordinating Center, University of Washington, 4311 11th Avenue NE #300, Seattle, WA 98105, USA
Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
* To whom correspondence should be addressed. kurland{at}u.washington.edu
For observational longitudinal studies of geriatric populations, outcomes such as disability or cognitive functioning are often censored by death. Statistical analysis of such data may explicitly condition on either vital status or survival time when summarizing the longitudinal response. For example a pattern-mixture model characterizes the mean response at time t conditional on death at time S = s (for s > t), and thus uses future status as a predictor for the time t response. As an alternative, we define regression conditioning on being alive as a regression model that conditions on survival status, rather than a specific survival time. Such models may be referred to as partly conditional since the mean at time t is specified conditional on being alive (S > t), rather than using finer stratification (S = s for s > t). We show that naive use of standard likelihood-based longitudinal methods and generalized estimating equations with non-independence weights may lead to biased estimation of the partly conditional mean model. We develop a taxonomy for accommodation of both dropout and death, and describe estimation for binary longitudinal data that applies selection weights to estimating equations with independence working correlation. Simulation studies and an analysis of monthly disability status illustrate potential bias in regression methods that do not explicitly condition on survival.
Keywords: Binary longitudinal data; Censoring; Dropout; Missing data
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  L. Su and J. W. Hogan Varying-coefficient models for longitudinal processes with continuous-time informative dropout Biostat., October 15, 2009; (2009) kxp040v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 K. L. Syrjala, B. F. Kurland, J. R. Abrams, J. E. Sanders, and J. R. Heiman Sexual function changes during the 5 years after high-dose treatment and hematopoietic cell transplantation for malignancy, with case-matched controls at 5 years Blood, February 1, 2008; 111(3): 989 - 996. [Abstract] [Full Text] [PDF]
|
|