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Activity Number:
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352
- Small Area Estimation, Analysis of Complex Sample Survey Data, and New Advances for Health Surveys
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Type:
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Contributed
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Date/Time:
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Thursday, August 12, 2021 : 10:00 AM to 11:50 AM
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Sponsor:
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Survey Research Methods Section
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Abstract #318563
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Title:
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Joinpoint Regression Methods of Aggregated Outcomes for Complex Survey Data
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Author(s):
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Benmei Liu* and Hyune-Ju Kim and Eric J. Feuer and Barry Graubard
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Companies:
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National Cancer Institute and Syracuse University and National Cancer Institute and National Cancer Institute, DCEG, Biostatistics Branch
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Keywords:
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Joinpoint regression;
variance-covariance matrix;
complex survey data
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Abstract:
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Joinpoint regression can model trends in time-specific estimates from aggregated data. These methods have been developed mainly for non-survey data such as cancer registry data assuming that the time-specific estimates are uncorrelated from time point to time point. This independence assumption can be violated for trends in time-specific estimates from complex survey samples due to using overlapping primary sampling units across time and, therefore, the variance-covariance matrix of the time-specific estimates should be incorporated into the regression model fitting. This paper extends these joinpoint methods for analyzing complex survey data within the National Cancer Institute’s Joinpoint software and empirically compares the extended method to existing methods for analyses of time trends in three surveys.
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Authors who are presenting talks have a * after their name.
