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Estimation of Covariate Effects With Current Status Data and Differential Mortality

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  • Alberto Palloni
  • Jason Thomas

Abstract

The assessment of the impact that socioeconomic determinants have on the prevalence of certain chronic conditions reported by respondents in population surveys must confront two problems. First, the self-reports could be in error (false positives and false negatives). Second, those reporting are a selected sample of those who ever experience the problem, and this selection is heavily influenced by excess mortality attributable to the condition being reported. In this article, we use a combination of empirical data and microsimulation to (a) assess the magnitude of the bias attributable to the selection problem, and (b) suggest an adjustment procedure that corrects for this bias. We find that the proposed adjustment procedure considerably reduces the bias arising from differential mortality. Copyright Population Association of America 2013

Suggested Citation

  • Alberto Palloni & Jason Thomas, 2013. "Estimation of Covariate Effects With Current Status Data and Differential Mortality," Demography, Springer;Population Association of America (PAA), vol. 50(2), pages 521-544, April.
    • Handle: RePEc:spr:demogr:v:50:y:2013:i:2:p:521-544
    DOI: 10.1007/s13524-012-0160-6
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    References listed on IDEAS

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    6. Robbins, J.M. & Vaccarino, V. & Zhang, H. & Kasl, S.V., 2001. "Socioeconomic status and type 2 diabetes in African American and non-Hispanic White women and men: Evidence from the Third National Health and Nutrition Examination Survey," American Journal of Public Health, American Public Health Association, vol. 91(1), pages 76-83.
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    Cited by:

    1. Ezra Fishman, 2017. "Risk of Developing Dementia at Older Ages in the United States," Demography, Springer;Population Association of America (PAA), vol. 54(5), pages 1897-1919, October.

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