AbstractDifferent distributions of confounding variables in populations complicate any comparison of the relative frequency of an event. To resolve this, methods for fitting statistical models to tables of rates have recently been developed. One such model is the multiplicative model. We performed a Monte Carlo study of the multiplicative model for a 4 × 3 table of rates. For small samples the likelihood ratio test statistic was conservative for small expected cell counts, liberal for moderate expected counts, and performed well for large expected counts. The weighted least squares test statistic was generally more conservative and less powerful than both the likelihood ratio statistic and the Pearson statistic