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Activity Number: 499
Type: Contributed
Date/Time: Wednesday, August 7, 2013 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract - #308307
Title: Applications of Survey Regression Models to Estimate the Degree of Data Agreement
Author(s): Julia Soulakova*+ and Peng Zhao
Companies: University of Nebraska-Lincoln and University of Nebraska-Lincoln
Keywords: complex design ; history of smoking ; data accuracy ; national survey ; smoking attributes

Test-retest reliability of survey data is commonly assessed using descriptive measures, such as intra-class correlation coefficient, kappa and Pearson correlation. In addition, logistic regression models can be used to estimate the odds ratios of agreement between responses reported repeatedly. In some cases regression models can be used to assess the magnitude of the difference between responses. While the model-based reliability analysis allows for controlling for multiple factors and identifying subpopulations and survey administration characteristics that contribute to the highest and lowest degree of agreement, as well as estimating the variance properly, they have certain limitations when used to describe the degree of data agreement. The goal of our talk is to discuss these approaches and illustrate their applications via examples using the Tobacco Use Supplement to the Current Population Survey data.

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

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