Robust Respondents and Lost Limitations: The Implications of Nonrandom Missingness for the Estimation of Health Trajectories.

TitleRobust Respondents and Lost Limitations: The Implications of Nonrandom Missingness for the Estimation of Health Trajectories.
Publication TypeJournal Article
Year of Publication2019
AuthorsJackson, HM, Engelman, M, Bandeen-Roche, K
JournalJournal of Aging and Health
Volume31
Issue4
Pagination685-708
ISSN Number1552-6887
KeywordsHealth Trajectories, Survey Methodology
Abstract

OBJECTIVE: We offer a strategy for quantifying the impact of mortality and attrition on inferences from later-life health trajectory models.

METHOD: Using latent class growth analysis (LCGA), we identify functional limitation trajectory classes in the Health and Retirement Study. We compare results from complete case and full information maximum likelihood (FIML) analyses, and demonstrate a method for producing upper- and lower-bound estimates of the impact of attrition on results.

RESULTS: LCGA inferences vary substantially depending on the handling of missing data. For older adults who die during the follow-up period, the widely used FIML approach may underestimate functional limitations by up to 20%.

DISCUSSION: The most commonly used approaches to handling missing data likely underestimate the extent of poor health in aging populations. Although there is no single solution for nonrandom missingness, we show that bounding estimates can help analysts to better characterize patterns of health in later life.

DOI10.1177/0898264317747079
User Guide Notes

http://www.ncbi.nlm.nih.gov/pubmed/29254422?dopt=Abstract

Alternate JournalJ Aging Health
Citation Key9456
PubMed ID29254422
PubMed Central IDPMC5984107