title: Approaches to handling incomplete data in family-based association testing.
abstract: The high throughput of data arising from the complete sequence of the human genome has left statistical geneticists with a rich and extensive information source. The wide availability of software and the increase in computing power has improved the possibilities to access and process such data. One problem is incompleteness of the data: unobserved or partially observed data points due to technical reasons or reasons associated with the patient's status or erroneous measurements of phenotype or genotype, to name a few. When not properly accounted for, these sources of incompleteness may seriously jeopardize the credibility of results from analyses. In this paper we provide some perspectives on the occurrence and analysis of different forms of incomplete data in family-based genetic association testing.
authors.affiliation: Department of Applied Mathematics and Computer Science, Ghent University, Ghent, Belgium.
authors.forename: K
authors.initials: K
authors.lastname: Van Steen
authors.forename: N M
authors.initials: NM
authors.lastname: Laird
authors.forename: P
authors.initials: P
authors.lastname: Markel
authors.forename: G
authors.initials: G
authors.lastname: Molenberghs
mesh_terms: D003627:Data Interpretation, Statistical; D005190:Family; D005260:Female; D005826:Genetics, Medical / Q000706:statistics & numerical data*; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D008297:Male; D015233:Models, Statistical