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https://doi.org/10.13094/SMIF-2019-00017
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Undercoverage of the elderly institutionalized population: The risk of biased estimates and the potentials of weighting
[journal article]
Abstract
In most social surveys, the elderly institutionalized population is not part of the target population because it is considered as hard-to-reach and hard-to-interview. The deliberate exclusion of institutionalized elderly from survey samples might cause bias, like previous studies investigating ins... view more
In most social surveys, the elderly institutionalized population is not part of the target population because it is considered as hard-to-reach and hard-to-interview. The deliberate exclusion of institutionalized elderly from survey samples might cause bias, like previous studies investigating institutionalized elderly persons and their transition to institutions implied. We use a Monte Carlo simulation based on cross-national samples of the Survey of Health, Ageing and Retirement in Europe (SHARE) to test whether the noncoverage and undercoverage of the elderly institutionalized population lead to biased estimates. Moreover, we examined to what extent weights could be used to correct for the underrepresentation of the institutionalized population. Our results show that noncoverage leads to biased estimates in two healthrelated variables. With respect to undercoverage, the precision of all estimates is better, especially if weights accounting for the hard-to-survey population are applied.... view less
Keywords
simulation; random sample; sample; Europe; retirement home for the elderly; survey; weighting; elderly; survey research; data capture; estimation; nursing home
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
coverage bias; Institutionalized population; Monte Carlo Simulation; retirement and nursing homes; SHARE; Survey of Health, Ageing and Retirement in Europe; Survey weighting
Document language
English
Publication Year
2019
Page/Pages
p. 1-19
Journal
Survey Methods: Insights from the Field (2019)
Issue topic
Probability and Nonprobability Sampling: Sampling of hard-to-reach survey populations
ISSN
2296-4754
Status
Published Version; peer reviewed