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Longitudinal data analysis using generalized linear models
SUMMARY This paper proposes an extension of generalized linear models to the analysis of longitudinal data. We introduce a class of estimating equations that give consistent estimates of theExpand
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Longitudinal data analysis for discrete and continuous outcomes.
TLDR
A class of generalized estimating equations (GEEs) for the regression parameters is proposed which are consistent and asymptotically Gaussian even when the time dependence is misspecified as we often expect. Expand
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Analysis of Longitudinal Data.
Correspondence analysis is an exploratory tool for the analysis of associations between categorical variables, the results of which may be displayed graphically. For longitudinal data, two types ofExpand
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Models for longitudinal data: a generalized estimating equation approach.
This article discusses extensions of generalized linear models for the analysis of longitudinal data. Two approaches are considered: subject-specific (SS) models in which heterogeneity in regressionExpand
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Ozone and short-term mortality in 95 US urban communities, 1987-2000.
CONTEXT Ozone has been associated with various adverse health effects, including increased rates of hospital admissions and exacerbation of respiratory illnesses. Although numerous time-seriesExpand
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Nonlinear Time Series : Nonparametric and Parametric Methods
Although Nonlinear Time Series is the only part of the title to appear on the spine of this new book by Fan and Yao, the word “nonparametric” in the subtitle really deserves top billing. There areExpand
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Temperature and mortality in 11 cities of the eastern United States.
Episodes of extremely hot or cold temperatures are associated with increased mortality. Time-series analyses show an association between temperature and mortality across a range of less extremeExpand
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Fine particulate air pollution and hospital admission for cardiovascular and respiratory diseases.
CONTEXT Evidence on the health risks associated with short-term exposure to fine particles (particulate matter < or =2.5 microm in aerodynamic diameter [PM2.5]) is limited. Results from the newExpand
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A regression model for time series of counts
SUMMARY This paper discusses a model for regression analysis with a time series of counts. Correlation is assumed to arise from an unobservable process added to the linear predictor in a log linearExpand
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Fine particulate air pollution and mortality in 20 U.S. cities, 1987-1994.
BACKGROUND Air pollution in cities has been linked to increased rates of mortality and morbidity in developed and developing countries. Although these findings have helped lead to a tightening ofExpand
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