title: Optimal selection of individuals for repeated covariate measurements in follow-up studies.
abstract: Repeated covariate measurements bring important information on the time-varying risk factors in long epidemiological follow-up studies. However, due to budget limitations, it may be possible to carry out the repeated measurements only for a subset of the cohort. We study cost-efficient alternatives for the simple random sampling in the selection of the individuals to be remeasured. The proposed selection criteria are based on forms of the D-optimality. The selection methods are compared with the simulation studies and illustrated with the data from the East-West study carried out in Finland from 1959 to 1999. The results indicate that cost savings can be achieved if the selection is focused on the individuals with high expected risk of the event and, on the other hand, on those with extreme covariate values in the previous measurements.
authors.affiliation: Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland jaakko.o.reinikainen@jyu.fi.
authors.forename: Jaakko
authors.initials: J
authors.lastname: Reinikainen
authors.affiliation: Department of Mathematics and Statistics, University of Jyväskylä, Jyväskylä, Finland.
authors.forename: Juha
authors.initials: J
authors.lastname: Karvanen
authors.affiliation: Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
authors.forename: Hanna
authors.initials: H
authors.lastname: Tolonen
mesh_terms: D000328:Adult; D002318:Cardiovascular Diseases / Q000401:mortality; D005387:Finland; D005500:Follow-Up Studies; D006801:Humans; D008875:Middle Aged; D018579:Patient Selection; D012107:Research Design; D012307:Risk Factors; D013997:Time Factors
keywords: data collection; follow-up study; missing covariate data; optimal design; repeated measurements