A simple approach to analyzing clustered longitudinal data

Autor:	Matthew Stephenson, Gerarda Darlington, R. Ayesha Ali
Rok vydání:	2015
Předmět:	Statistics and Probability Longitudinal data Estimation theory Simple (abstract algebra) Modeling and Simulation Resampling Binary data Statistics Cluster (physics) Constant (mathematics) Generalized estimating equation Mathematics
Zdroj:	Communications in Statistics - Simulation and Computation. :1-10
ISSN:	1532-4141 0361-0918
DOI:	10.1080/03610918.2015.1096380
Popis:	When modeling correlated binary data in the presence of informative cluster sizes, generalized estimating equations with either resampling or inverse-weighting, are often used to correct for estimation bias. However, existing methods for the clustered longitudinal setting assume constant cluster sizes over time. We present a subject-weighted generalized estimating equations scheme that provides valid parameter estimation for the clustered longitudinal setting while allowing cluster sizes to change over time. We compare, via simulation, the performance of existing methods to our subject-weighted approach. The subject-weighted approach was the only method that showed negligible bias, with excellent coverage, for all model parameters.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::143ec93ccbb2ba6a2da6b9806cb89a7f https://doi.org/10.1080/03610918.2015.1096380 Zobrazit plný text záznamu