A two-stage approach to the correction of ascertainment bias in complex genetic studies involving variance components

J. Bowden*, J. R. Thompson, P. R. Burton

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

2 Citations (Scopus)

Abstract

Correction for ascertainment bias is a vital part of the analysis of genetic epidemiology studies that needs to be undertaken whenever subjects are not recruited at random. Adjustment often requires extensive numerical integration, which can be very slow or even computationally infeasible, especially if the model includes many fixed and random effects. In this paper we propose a two-stage method for ascertainment bias correction. In the first stage we estimate parameters that pertain to the ascertained population, that is the population that would be selected into the sample if the ascertainment criterion were applied to everyone. In the second stage we convert the estimates for the ascertained population into general population parameter estimates. We illustrate the method with simulations based on a simple model and then describe how the method can be used with complex models. The two-stage approach avoids some of the integration required in direct adjustment, hence speeding up the process of model fitting.

Original languageEnglish
Pages (from-to)220-229
Number of pages10
JournalAnnals of Human Genetics
Volume71
Issue number2
DOIs
Publication statusPublished - 1 Mar 2007

Fingerprint Dive into the research topics of 'A two-stage approach to the correction of ascertainment bias in complex genetic studies involving variance components'. Together they form a unique fingerprint.

Cite this