Goetghebeur and Ryan proposed a method for proportional hazards analyses of competing risks failuretime data when the failure type is missing for some cases. This paper evaluates the properties of the method using data from a clinical trial in Hodgkin's disease. We generated several patterns of miss
Haplotype analysis in the presence of informatively missing genotype data
β Scribed by Nianjun Liu; Isabel Beerman; Richard Lifton; Hongyu Zhao
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 231 KB
- Volume
- 30
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
β¦ Synopsis
Abstract
It is common to have missing genotypes in practical genetic studies, but the exact underlying missing data mechanism is generally unknown to the investigators. Although some statistical methods can handle missing data, they usually assume that genotypes are missing at random, that is, at a given marker, different genotypes and different alleles are missing with the same probability. These include those methods on haplotype frequency estimation and haplotype association analysis. However, it is likely that this simple assumption does not hold in practice, yet few studies to date have examined the magnitude of the effects when this simplifying assumption is violated. In this study, we demonstrate that the violation of this assumption may lead to serious bias in haplotype frequency estimates, and haplotype association analysis based on this assumption can induce both falseβpositive and falseβnegative evidence of association. To address this limitation in the current methods, we propose a general missing data model to characterize missing data patterns across a set of two or more markers simultaneously. We prove that haplotype frequencies and missing data probabilities are identifiable if and only if there is linkage disequilibrium between these markers under our general missing data model. Simulation studies on the analysis of haplotypes consisting of two single nucleotide polymorphisms illustrate that our proposed model can reduce the bias both for haplotype frequency estimates and association analysis due to incorrect assumption on the missing data mechanism. Finally, we illustrate the utilities of our method through its application to a real data set. Genet. Epidemiol. 2006. Β© 2006 WileyβLiss, Inc.
π SIMILAR VOLUMES
We describe a novel method for assessing the strength of disease association with single nucleotide polymorphisms (SNPs) in a candidate gene or small candidate region, and for estimating the corresponding haplotype relative risks of disease, using unphased genotype data directly. We begin by estimat
## Abstract We investigated the effect of multiple susceptibility alleles at a single disease locus on the statistical power of a likelihood ratio test to detect association between alleles at a marker locus and a disease phenotype in a caseβcontrol design. Using simplifying assumptions to obtain t