The article by Devlin and Risch compares five measures of linkage disequilibrium (LD) for fine-scale mapping of disease genes: Δ (the correlation coefficient), D' (Lewontin's D'), δ (the robust formulation of the population attributable risk), Q (Yule's Q), and d (Kaplan and Weir's proportional difference). The study investigates the performance of these measures under the assumption of initial complete LD between the disease and marker loci. δ is found to be the most superior measure for fine mapping because it is directly related to the recombination fraction and remains invariant when disease haplotypes are sampled at a higher rate than their population frequencies, as in case-control studies. D' yields comparable results to δ in many realistic settings. Among the remaining measures, Q shows the best performance. The article also discusses the impact of marker allele frequencies and evolutionary forces on the accuracy of LD measures, emphasizing that δ and D' are more robust to such variations compared to other measures. The findings highlight the importance of choosing an appropriate LD measure for accurate fine mapping.The article by Devlin and Risch compares five measures of linkage disequilibrium (LD) for fine-scale mapping of disease genes: Δ (the correlation coefficient), D' (Lewontin's D'), δ (the robust formulation of the population attributable risk), Q (Yule's Q), and d (Kaplan and Weir's proportional difference). The study investigates the performance of these measures under the assumption of initial complete LD between the disease and marker loci. δ is found to be the most superior measure for fine mapping because it is directly related to the recombination fraction and remains invariant when disease haplotypes are sampled at a higher rate than their population frequencies, as in case-control studies. D' yields comparable results to δ in many realistic settings. Among the remaining measures, Q shows the best performance. The article also discusses the impact of marker allele frequencies and evolutionary forces on the accuracy of LD measures, emphasizing that δ and D' are more robust to such variations compared to other measures. The findings highlight the importance of choosing an appropriate LD measure for accurate fine mapping.