The incorporation of covariate information into a linkage analysis can potentially increase the power to detect linkage by identifying more loci with linkage evidence and also increased statistical linkage evidence for identified loci. Because the addition of each covariate into the analysis inflates the type I error rate in this likelihood model, it is important to use empirically derived p-values to determine significance. Having corrected for the inflation in the type I error rate, the use of a propensity score (except for PS2) compared with the use of all the covariate simultaneously does lead to the identification of more linked loci in this study. Even though several regions of significant linkage were consistent across the analysis methods, the location of the most significant regions was not consistent. Thus it is also important to emphasize that despite the power increase, the selection of covariates to include into the analysis method must be done carefully and the identification of the significant linkage regions can vary based on the covariates used. However, defining a PS that results in the covariates having the largest
