Assessing Variability Due to Race Bridging

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Abstract
In 1997, the Office of Management and Budget revised the standards for classification of Federal data on race and ethnicity. A key provision of the revised standards is that each respondent in a Federal data collection is now allowed to select more than one race to describe the person in question. The prior standards, published in 1977, specified that each respondent be instructed to select only one race. In the 2000 census, data on race were collected under the new standards. To make the 2000 census data compatible with other data systems that have not yet implemented the new standards as well as with historical data collected under the prior standards, the National Center for Health Statistics of the Centers for Disease Control and Prevention, with assistance from the Bureau of the Census, has produced bridged census counts, that is, estimates of the counts by race that would have been obtained had the prior standards been in effect. This article presents techniques for assessing the variability due to race bridging. The methods developed by Schafer and Schenker for inference with imputed conditional means, which can be considered a first-order approximation to a multiple-imputation analysis with an infinite number of imputations, are adapted to the bridging problem and applied to bridged 2000 census counts as well as to selected vital rates for 2000 computed using bridged census counts as denominators. The relative standard errors of estimated census counts by race under the 1977 standards tend to be higher for finer geographic levels and lower for coarser geographic levels. For each state (or the District of Columbia), the relative standard error of the count for a given race is no greater than .05. For birth and death rates by age group and 1977 race at the national level, on an absolute basis, bridging of the census counts in the denominators does not add substantially to the relative standard errors.

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