It is well known that linkage analysis using simple random sib-pairs has relatively low power for detecting quantitative trait loci with small genetic effects. The power can be substantially increased by using samples selected based on their trait values. Usually, samples that are obtained by truncation selection consist of random samples from a truncated trait distribution. In this article we propose an alternative method using extreme ranks for linkage analysis with selected sib-pairs. This approach approximates the truncation selection. With similar screening sizes and the same sample size of selected sib-pairs, the extreme rank selection and truncation method have similar power performance, both of which are substantially more powerful than when using random sib-pairs. Simulation results on the comparison of powers between the truncation selection and the extreme rank selection and/or random selection for linkage analysis are reported.