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Activity Number: 237 - SPEED: Missing Survey Data: Analysis, Imputation, Design, and Prevention
Type: Contributed
Date/Time: Monday, July 30, 2018 : 2:00 PM to 3:50 PM
Sponsor: Survey Research Methods Section
Abstract #329046
Title: Nonresponse Bias Analysis for the Medicare Current Beneficiary Survey
Author(s): Kirk Wolter* and Ying Li and Whitney Murphy
Companies: NORC at the University of Chicago and NORC at the University of Chicago and NORC at the University of Chicago
Keywords: non-respondents; hard-to-contact respondents; longitudinal study; attrition rate; attributes; differences

Survey nonresponse occurs when data are not collected for an eligible sampled individual. If non-respondents differ from respondents in meaningful ways, then nonresponse bias may occur. This paper focuses on evaluating the presence and extent of unit nonresponse bias in the Medicare Current Beneficiary Survey (MCBS). The MCBS is a continuous, multipurpose survey of a nationally representative sample of the Medicare population, conducted by the Centers for Medicare & Medicaid Services through a contract with NORC at the University of Chicago. Unlike most nonresponse bias analyses that only have limited types of data available to conduct comparisons between respondents and non-respondents, the MCBS offers a variety of measures, such as demographic characteristics, self-reported attributes, Medicare administrative Fee-For-Service payment information, and administrative chronic conditions indicators to do analysis. We applied Rao-Scott chi-square test, adjusted logistic regression model, and generalized linear model with contrast analysis to identify statistically significant differences. Using these additional measures, we found that only limited attributes would indicate bias.

Authors who are presenting talks have a * after their name.

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