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5. Conclusion The proposed BUGS code provides an easy and efficient way to account for extended family structures in linear mixed models. Results from a real data set as well as simulation data show that this implementation produces consistent results with the classical linear mixed models in R. The usefulness of this approach is that it allows for linear mixed modeling of family-based data in the BUGS software, and thus possibly facilitates the use of Bayesian modeling of family-based data. The advantage of the Bayesian approach is that it provides an estimate of heritability but implementation is often challenging. We also illustrate the extension of our approach to generalized linear models that can be efficiently implemented in BUGS. Conflict of interest statement The authors declare that the research was conducted in click here the absence of any commercial or financial relationships Metalloexopeptidase that could be construed as a potential conflict of interest. Acknowledgments This work was funded by the National Institute on Aging (NIA U19-AG023122, U01-AG023755 to Thomas T. Perls), the National Heart Lung Blood Institute (R21HL114237 to Paola Sebastiani), and the National Institure of General Medical Sciences T32GM074905. Supplemental data Sample R script for computing the singular value decomposition of the additive genetic relationship matrix.## Read the Phenotype Data ##pheno.file selleck products This creates the kinship matrixkmat.full