effects as described in the previous section. This allows an estimate of county-specific, expected suicide rates, which directly incorporate the effects race, sex, and age of that county. Table 10-2 provides a comparison of observed and expected numbers of suicides (1996-1998) for 100 randomly selected counties. Inspection of Table 10-2 reveals remarkably close agreement between observed and expected numbers of suicides.

This approach also allows the use of Bayes estimates directly to obtain county-level suicide rates adjusted for the effects of race, sex, and age. For example, a Bayes estimate of 1.0 represents an adjusted rate that is equal to the national rate, while a Bayes estimate of 2.0 represents a doubling of the national rate, and a Bayes estimate of 0.5 represents one-half of the national rate. Figure 10-1 (found on page 382) displays the Bayes estimates by county across the United States and reveals that even after accounting for these important demographic variables, considerable spatial variability remains. This map provides a useful tool for qualitative research into the etiology of suicide through an assessment of the spatial