Full Citation

Title: Joinpoint Regression Methods of Aggregate Outcomes for Complex Survey Data

Citation Type: Journal Article

Publication Year: 2022

ISBN:

ISSN: 2325-0984

DOI: 10.1093/JSSAM/SMAC014

NSFID:

PMCID:

PMID:

Abstract: Joinpoint regression can model trends in time-specific estimates from aggregated data. These methods have been developed mainly for nonsurvey 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 the same primary sampling units across time and, therefore, the full variance–covariance matrix of the time-specific estimates should be incorporated into the regression model fitting. This article 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.

Url: https://academic.oup.com/jssam/advance-article/doi/10.1093/jssam/smac014/6608689

User Submitted?: No

Authors: Liu, Benmei; Kim, Hyune-Ju; Feuer, Eric J.; Graubard, Barry I.

Periodical (Full): Journal of Survey Statistics and Methodology

Issue: 4

Volume: 11

Pages: 1-23

Data Collections: IPUMS Health Surveys - NHIS

Topics: Methodology and Data Collection, Population Data Science

Countries: