title: Informative missingness in genetic association studies: case-parent designs.
abstract: We consider the effect of informative missingness on association tests that use parental genotypes as controls and that allow for missing parental data. Parental data can be informatively missing when the probability of a parent being available for study is related to that parent's genotype; when this occurs, the distribution of genotypes among observed parents is not representative of the distribution of genotypes among the missing parents. Many previously proposed procedures that allow for missing parental data assume that these distributions are the same. We propose association tests that behave well when parental data are informatively missing, under the assumption that, for a given trio of paternal, maternal, and affected offspring genotypes, the genotypes of the parents and the sex of the missing parents, but not the genotype of the affected offspring, can affect parental missingness. (This same assumption is required for validity of an analysis that ignores incomplete parent-offspring trios.) We use simulations to compare our approach with previously proposed procedures, and we show that if even small amounts of informative missingness are not taken into account, they can have large, deleterious effects on the performance of tests.
authors.affiliation: Department of Biostatistics and Bioinformatics and Duke Clinical Research Institute, Duke University Medical Center, Durham, NC, USA.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Allen
authors.forename: Paul J
authors.initials: PJ
authors.lastname: Rathouz
authors.forename: Glen A
authors.initials: GA
authors.lastname: Satten
mesh_terms: D003198:Computer Simulation; D005260:Female; D030342:Genetic Diseases, Inborn / Q000235:genetics*; D005838:Genotype; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D009679:Nuclear Family; D010290:Parents; D011336:Probability