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Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims

Kurland, Brenda F. and Johnson, Laura L. and Egleston, Brian L. and Diehr, Paula H. (2009) Longitudinal Data with Follow-up Truncated by Death: Match the Analysis Method to Research Aims. Statistical Sciences, 24 (2). pp. 211-222. ISSN 0883-4237

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Abstract

Diverse analysis approaches have been proposed to distinguish data missing due to death from nonresponse, and to summarize trajectories of longitudinal data truncated by death. We demonstrate how these analysis approaches arise from factorizations of the distribution of longitudinal data and survival information. Models are illustrated using cognitive functioning data for older adults. For unconditional models, deaths do not occur, deaths are independent of the longitudinal response, or the unconditional longitudinal response is averaged over the survival distribution. Unconditional mod- els, such as random effects models fit to unbalanced data, may implicitly impute data beyond the time of death. Fully conditional models stratify the longitudinal response trajectory by time of death. Fully conditional models are effective for describing in- dividual trajectories, in terms of either aging (age, or years from baseline) or dying (years from death). Causal models (principal stratification) as currently applied are fully conditional models, since group differences at one timepoint are described for a cohort that will survive past a later timepoint. Partly conditional models summarize the longitudinal response in the dynamic cohort of survivors. Partly conditional models are serial cross-sectional snapshots of the response, reflecting the average response in survivors at a given timepoint rather than individual trajectories. Joint models of sur- vival and longitudinal response describe the evolving health status of the entire cohort. Researchers using longitudinal data should consider which method of accommodating deaths is consistent with research aims, and use analysis methods accordingly.

Item Type: Article
Additional Information: This article is freely available via Project Euclid.
DOI: 10.1214/09-STS293
PubMed ID: 20119502
NIHMSID: NIHMS142962
PMCID: PMC2812934
Grant Numbers: P30 CA 06927, N01-HC- 85079, N01-HC-85086, N01-HC-35129, N01 HC-15103, N01 HC-55222, N01-HC-75150, N01-HC- 45133, U01 HL080295
Depositing User: Library Staff
Date Deposited: 22 Feb 2010 20:25
Last Modified: 14 Feb 2012 14:42
URI: http://authors.fhcrc.org/id/eprint/329

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