Random effects model for meta-analysis of multiple quantitative sibpair linkage studies

The growing interest in detection of genetic effects for complex traits along with molecular revolution has stimulated many linkage studies. Multiple replication studies tend to produce different results. In such situations, rigorous meta-analysis methods can be useful for assessing the overall evidence for linkage. We propose here a random effects model for combining results from independent quantitative sibpair linkage studies. The model can be used to assess the aggregate evidence for linkage by combing the regression coefficients to the Haseman and Elston [(1972) Behav Genet 2:3-19] sibpair method as well as to assess heterogeneity among the multiple studies.