JSM 2005 - Toronto

Abstract #303554

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Activity Number: 18
Type: Topic Contributed
Date/Time: Sunday, August 7, 2005 : 2:00 PM to 3:50 PM
Sponsor: Section on Government Statistics
Abstract - #303554
Title: Assessing the Impact of High-effort Interviews on Health Estimates
Author(s): Catherine Simile*+ and James Dahlhamer and Pei-Lu Chiu and Gulnur Scott
Companies: National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics and National Center for Health Statistics
Address: 3311 Toledo Road, Hyattsville, MD, 20782, United States
Keywords: nonresponse bias ; data quality ; survey nonresponse ; item nonresponse
Abstract:

Several methodologies have emerged to estimate differences between survey respondents and nonrespondents, including comparisons of "difficult" versus "easy" interviews. Using 2004 data from the National Health Interview Survey (NHIS), an ongoing population-based health survey conducted by the National Center for Health Statistics, and using data from the associated Contact History Instrument, we assess the impact that high effort, difficult cases have on data quality and utility. First, we determine the impact the removal of these cases has on selected sociodemographic and health estimates: Do the estimates change significantly if we expend less effort to keep these cases? This bias is important to determine in an era of decreasing unit response rates. Second, to measure quality, we explore the extent of item missingness in the difficult, high-effort cases: Do these cases produce more item nonresponse? This is important to determine because, in addition to a loss of power and efficiency, if item nonresponse increases with efforts to improve unit nonresponse, the loss of difficult cases during multivariate analysis may produce the biased estimates one was attempting to avoid.

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Revised March 2005