Criteria for comparing the utility of this and existing indexes of association are reviewed. The theoretical distribution of RIOC for large and small sample sizes is presented and tested against the results from computer- generated tables. Methods are presented for calculating confidence intervals for RIOC, for testing the significance of individual values of RIOC, and for testing the difference between several values of RIOC from various studies. RIOC has a number of advantages over existing indices of predictive association, particularly since it combines a correction for chance and for differences in maximum values in 2x2 tables. Whereas many prediction indices correct for chance, RIOC has the unique advantage of correcting for the maximum value that results from a distinct discrepancy between base rate and selection ratio. RIOC also provides for the possibility to calculate confidence intervals and to test the statistical significance between several RIOC's. Advances presented in this paper will help researchers to use RIOC more judiciously in coming to valid conclusions about the strength of predictive association in 2x2 tables or in meta-analyses. 4 tables, 1 figure, and 22 references
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