Sib pairs drawn from the simulated common oligogenic disease families were selected for extreme quantitative trait scores and analyzed using interval mapping and multipoint methods. Linkage analyses of 112 selected sib pairs, in which one or more members had trait values exceeding the disease threshold, were compared with analyses of the total unselected sib-pair sample (771 pairs). Selected sample regression models yielded comparable significance levels to those obtained from the unselected sample at most loci on the six simulated chromosomes, demonstrating the efficiency of selected sib-pair analysis for quantitative characters. Two of the three disease QTLs were detected in both selected and unselected samples. Interval mapping and multipoint analyses yielded location estimates close to the simulated positions of the QTLs. The combined strategy of using interval mapping and multipoint methods with selected sib pairs appears to provide improved accuracy and sensitivity over more traditional sib-pair methods for detecting quantitative trait loci.