NDLI: Estimating health expectancy in presence of missing data: an application using HID survey

Content Provider	Springer Nature Link
Author	Giudici, Cristina Arezzo, Maria Felice Brouard, Nicolas
Copyright Year	2013
Abstract	In this article we estimate health transition probabilities using longitudinal data collected in France for the survey on handicaps, disabilities and dependencies from 1998 to 2001. Life expectancies with and without disabilities are estimated using a Markov-based multi-state life table approach with two non-absorbing states: able to perform all activities of daily living (ADLs) and unable or in need of help to perform one or more ADLs, and the absorbing state of death. The loss of follow-up between the two waves induces biases in the probabilities estimates: mortality estimates were biased upwards; also the incidence of recovery and the onset of disability seemed to be biased. Since individuals were not missing completely at random, we correct this bias by estimating health status for drop-outs using a non parametric model. After imputation, we found that at the age of 70 disability-free life expectancy decreases by 0.5 years, whereas the total life expectancy increases by 1 year. The slope of the stable prevalence increases, but it remains lower than the slope of the cross sectional prevalence. The gender differences on life expectancy did not change significantly after imputation. Globally, there is no evidence of a general reduction in ADL disability, as defined in our study. The added value of the study is the reduction of the bias induced by sample attrition.
Starting Page	517
Ending Page	534
Page Count	18
File Format	PDF
ISSN	16182510
Journal	Statistical Methods and Applications
Volume Number	22
Issue Number	4
e-ISSN	1613981X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2013-07-09
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Healthy life expectancy Classification and regression trees Sample attrition Statistics Statistics for Business/Economics/Mathematical Finance/Insurance Economic Theory
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Statistics, Probability and Uncertainty

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