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The impact of data suppression on local mortality rates: The case of cdc wonder

Author

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  • Tiwari, C.
  • Beyer, K.
  • Rushton, G.

Abstract

CDC WONDER (Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research) is the nation's primary data repository for health statistics. Before WONDER data are released to the public, data cells with fewer than 10 case counts are suppressed. We showed that maps produced from suppressed data have predictable geographic biases that can be removed by applying population data in the system and an algorithm that uses regional rates to estimate missing data. By using CDC WONDER heart disease mortality data, we demonstrated that effects of suppression could be largely overcome.

Suggested Citation

  • Tiwari, C. & Beyer, K. & Rushton, G., 2014. "The impact of data suppression on local mortality rates: The case of cdc wonder," American Journal of Public Health, American Public Health Association, vol. 104(8), pages 1386-1388.
    • Handle: RePEc:aph:ajpbhl:10.2105/ajph.2014.301900_9
    DOI: 10.2105/AJPH.2014.301900
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    Cited by:

    1. Zhai, Muxin & Kishan, Ruby P. & Showalter, Dean, 2022. "Social capital and suicidal behaviors: Evidence from the United States counties," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 98(C).
    2. Ioana Popescu & Erin Duffy & Joshua Mendelsohn & José J Escarce, 2018. "Racial residential segregation, socioeconomic disparities, and the White-Black survival gap," PLOS ONE, Public Library of Science, vol. 13(2), pages 1-15, February.

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