Literature DB >> 15669746

Telephone service interruption weighting adjustments for state health insurance surveys.

Michael Davern1, James Lepkowski, Kathleen Thiede Call, Noreen Arnold, Tracy L Johnson, Karen Goldsteen, April Todd-Malmlov, Lynn A Blewett.   

Abstract

Many states rely on telephone surveys to produce estimates of uninsurance. To the extent that people in households without telephones differ from those living in households with telephones, estimates will be biased due to lack of coverage of those in households without telephones. We find the disparity in estimates of uninsurance in the Current Population Survey (all people vs. those living in households without telephones) shows a similar association to the disparity found in the state surveys (all people vs. those living in households with telephone service interruptions). We adjust the state survey weights of those people living in households that experienced telephone interruptions to account for people living in households without telephones and evaluate whether the weighting adjustment for telephone service interruptions is advisable.

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Year:  2004        PMID: 15669746

Source DB:  PubMed          Journal:  Inquiry        ISSN: 0046-9580            Impact factor:   1.730


  4 in total

1.  Health Insurance Dynamics: Methodological Considerations and a Comparison of Estimates from Two Surveys.

Authors:  John A Graves; Pranita Mishra
Journal:  Health Serv Res       Date:  2016-02-03       Impact factor: 3.402

2.  Meeting the need for state-level estimates of health insurance coverage: use of State and Federal survey data.

Authors:  Lynn A Blewett; Michael Davern
Journal:  Health Serv Res       Date:  2006-06       Impact factor: 3.402

3.  Implications of the Medicaid undercount in a high-penetration Medicaid state.

Authors:  R Kirby Goidel; Steven Procopio; Douglas Schwalm; Dek Terrell
Journal:  Health Serv Res       Date:  2007-12       Impact factor: 3.402

4.  Reevaluating the need for concern regarding noncoverage bias in landline surveys.

Authors:  Stephen J Blumberg; Julian V Luke
Journal:  Am J Public Health       Date:  2009-08-20       Impact factor: 9.308

  4 in total

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