CHROMSCAN implements a composite likelihood model for the analysis of association data. Disease-gene localisation is on a linkage disequilibrium unit (LDU) map, and locations and standard errors, for putatively causal polymorphisms, are determined by the programme. Distortions of the probability distribution created by auto-correlation are avoided by implementation of a permutation test. We evaluated the relative efficiency of the LDU map by simulating pseudo-phenotypes in real genotype samples. We observed that multi-locus mapping on an underlying LDU map reduces location error by approximately 46%. Furthermore, there is a small, but significant, increase in power of approximately 5%. Effective meta-analysis across multiple samples, increasingly important to combine evidence from genome-wide and other association data, is achieved through the weighted combination of location evidence provided by the programme.