期刊
STAT
卷 4, 期 1, 页码 1-14出版社
WILEY
DOI: 10.1002/sta4.73
关键词
health examination survey; missing data; non-participation; registry data; smoking prevalence; survey sampling
资金
- Academy of Finland [266251]
Data missing not at random (MNAR) are a major challenge in survey sampling. We propose an approach based on registry data to deal with non-ignorable missingness in health examination surveys. The approach relies on follow-up data available from administrative registers several years after the survey. For illustration, we use data on smoking prevalence in Finnish National FINRISK study conducted in 1972-97. The data consist of measured survey information including missingness indicators, register-based background information and register-based time-to-disease survival data. The parameters of missingness mechanism are estimable with these data although the original survey data are MNAR. The underlying data generation process is modelled by a Bayesian model. The results indicate that the estimated smoking prevalence rates in Finland may be significantly affected by missing data. Copyright (C) 2015 John Wiley & Sons, Ltd.
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