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How to deal with missing longitudinal data in cost of illness analysis in Alzheimer's disease-suggestions from the GERAS observational study
Abstract
Missing data are a common problem in prospective studies with a long follow-up, and the volume, pattern and reasons for missing data may be relevant when estimating the cost of illness. We aimed to evaluate the effects of different methods for dealing with missing longitudinal cost data and for costing caregiver time on total societal costs in Alzheimer's disease (AD)- info:eu-repo/semantics/article
- alzheimer’s disease
- cost of illne
- missing data analysi
- missing data mechanism
- multiple imputation
- alzheimer disease
- caregiver
- cost-benefit analysi
- data accuracy
- health care cost
- human
- independent living
- longitudinal studie
- markov chain
- middle aged
- monte carlo method
- observational studies as topic
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Last time updated on 18/04/2018
This paper was published in Archivio della ricerca- Università di Roma La Sapienza.
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