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Poverty and InequalitySexual and Reproductive HealthFamily, Maternal & Child HealthMethodology

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 Publication2017
AuthorsJackson, H, Engelman, M, Bandeen-Roche, K
JournalJ Aging Health
Pagination898264317747079
Date PublishedDec 1
ISBN Number0898-2643
Accession Number29254422
Keywordslatent class growth analysis, Longitudinal analysis, mortality and attrition bias
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.

PMCID

PMC5984107