Evidence map›Paper›PMID 29254422›Full record

ArticleJournal of aging and health2019

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

Heide Jackson, Michal Engelman, Karen Bandeen-Roche

Abstract read
In one paragraph

Article in Journal of aging and health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Health, Wealth, and Voting Trajectories in Later Life.The journals of gerontology. Series B, Psychological sciences and social sciences · 2022
    Article
  9. Deaths, Disparities, and Cumulative (Dis)Advantage: How Social Inequities Produce an Impairment Paradox in Later Life.The journals of gerontology. Series A, Biological sciences and medical sciences · 2022
    Article
  10. Observational
  11. Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Heide Jackson1 University of Wisconsin-Madison, USA.
Michal Engelman1 University of Wisconsin-Madison, USA.
Karen Bandeen-Roche2 Johns Hopkins University, Baltimore, MD, USA.

Funding

'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI BANDEEN-ROCHE, KAREN J. · 1985 to 2019
$37.6M
Research Education ComponentP30AG066507 · NIA · JOHNS HOPKINS UNIVERSITY · PI Corinne Pettigrew · 2020 to 2026
$29.3M
Statistical Data Enclave CoreP30AG017266 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1999 to 2026
$17.0M
EPIDEMIOLOGY AND BIOSTATISTICS OF AGINGT32AG000247 · NIA · JOHNS HOPKINS UNIVERSITY · PI Karen J. Bandeen-Roche · 1996 to 2026
$13.2M
Center for Demography and EcologyR24HD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI RAYMO, JAMES M · 2004 to 2013
$7.2M
POPULATION, LIFE COURSE, AND AGINGT32AG000129 · NIA · UNIVERSITY OF WISCONSIN-MADISON · PI Michal Engelman · 1986 to 2026
$6.0M
Network on Life Course Health Dynamics and Disparities in 21st Century America RenewalR24AG045061 · NIA · UNIVERSITY OF SOUTHERN CALIFORNIA · PI JENNIFER A AILSHIRE, Sarah A. Burgard · 2014 to 2026
$5.2M
Scientific and Technical CoreP2CHD047873 · NICHD · UNIVERSITY OF WISCONSIN-MADISON · PI Katherine J. Curtis · 2014 to 2026
$5.1M
NIA NIH HHS P30 AG017266NIA NIH HHS P30 AG066507NIA NIH HHS P50 AG005146NIA NIH HHS R24 AG045061NIA NIH HHS T32 AG000129NIA NIH HHS T32 AG000247NICHD NIH HHS P2C HD047873NICHD NIH HHS R24 HD047873
6 · The paper itself

Abstract

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

methodUsing 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.

resultsLCGA 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.

Indexed as

Data Interpretation, StatisticalAgedAgingData CollectionFemaleHealth StatusHumansMaleModels, StatisticalSurveys and Questionnaireslatent class growth analysislongitudinal analysismortality and attrition bias

Identifiers

PMID29254422
PMCPMC5984107

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.