title: Analysis of incomplete public health data.
abstract: The problem of dealing with missing values is common throughout statistics and is very prominent with epidemiologic data in the broad sense. Not only do data collection procedures break down, but subjects may be lost to follow up, or simply withdraw their consent without further providing a reason for doing so. In this paper, we review a framework for handling incomplete studies, and then concentrate on a specific case. It comes from a complex health interview survey, conducted in Belgium in 1997, where different types of missingness arise at various levels of the hierarchical sampling procedure.
authors.affiliation: Biostatistics, Center for Statistics, Limburgs Universitair Centrum, Universitaire Campus, B-3590 Diepenbeek, Belgium.
authors.forename: G
authors.initials: G
authors.lastname: Molenberghs
authors.forename: T
authors.initials: T
authors.lastname: Burzykowski
authors.forename: B
authors.initials: B
authors.lastname: Michiels
authors.forename: M G
authors.initials: MG
authors.lastname: Kenward
mesh_terms: D001530:Belgium; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D011634:Public Health / Q000706:statistics & numerical data*