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Activity Number:
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314
- Pioneering Statistical Methods to Alleviate Health Disparity and Achieve Health Equity
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Type:
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Invited
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Date/Time:
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Tuesday, August 9, 2022 : 2:00 PM to 3:50 PM
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Sponsor:
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Health Policy Statistics Section
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Abstract #319186
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Title:
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Health Disparity for Complex Survey Data
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Author(s):
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Barry Graubard and Joseph L. Gastwirth and Mi-Ok Kim and Hyokyoung (Grace) Hong*
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Companies:
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National Cancer Institute (NCI) and The George Washington University and UCSF and NCI/NIH
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Keywords:
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Peters-Belson;
Health disparity;
NHANES;
Survey data;
sample weights;
Oaxaca decomposition
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Abstract:
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We introduce approaches to measure the extent of explained and unexplained disparity on the various outcomes types between majority and minority groups. In addition, when using complex survey data ignoring the differential sampling rates (i.e., sample weights) and cluster sampling can result in biased disparity estimation and underestimation of their variances leading to incorrect inferences. The proposed disparity functions consider the complex, multistage probability sampling designs of surveys to properly estimate the disparity between majority and minority groups and its standard error across the different quantiles. We demonstrate the utility of the proposed quantile disparity approach using the National Health and Nutrition Examination Survey data.
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Authors who are presenting talks have a * after their name.
