Abstract
Racial classification is a paramount concern in data collection and analysis for American Indians and Alaska Natives (AI/ANs) and has far-reaching implications in health research. We examine how different racial classifications affect survey weights and consequently change health-related indicators for the AI/AN population in California. Using a very large random population-based sample of AI/ANs, we compared the impact of three weighting strategies on counts and rates of selected health indicators. We found that different weights examined in this study did not change the percentage estimates of health-related variables for AI/ANs, but did influence the population total estimates dramatically. In survey data, different racial classifications and tabulations of AI/ANs could yield discrepancies in weighted estimates for the AI/AN population. Policy makers need to be aware that the choice of racial classification schemes for this racial-political group can generally influence the data they use for decision making.
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