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2001
Abstract Counts of brain cancer incidence cases and deaths were recorded as part of the Surveillance, Epidemiology, and End Results (SEER) program of the Bio metry Branch of the National Cancer Institute. The SEER program acquired these incidence data from a number of surveyed areas in the United States (for example, the state of ...
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Abstract Counts of brain cancer incidence cases and deaths were recorded as part of the Surveillance, Epidemiology, and End Results (SEER) program of the Bio metry Branch of the National Cancer Institute. The SEER program acquired these incidence data from a number of surveyed areas in the United States (for example, the state of ...
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Sparse Bayesian Learning-Based Kernel Poisson Regression
IEEE Transactions on Cybernetics, 2019In this paper, we introduce a closed-form sparse Bayesian kernel Poisson regression (SBKPR) model for count data regression problems based on the sparse Bayesian learning (SBL) approach.
Yuheng Jia +4 more
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A new adjusted Liu estimator for the Poisson regression model
Concurrency and Computation, 2021Muhammad Amin, M. Akram, B. G. Kibria
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2008
Epidemiological studies often involve the calculation of rates, typically rates of death or incidence rates of a chronic or acute disease. This is based upon counts of events occurring within a certain amount of time. The Poisson regression method is often employed for the statistical analysis of such data. However, data that are not actually counts of
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Epidemiological studies often involve the calculation of rates, typically rates of death or incidence rates of a chronic or acute disease. This is based upon counts of events occurring within a certain amount of time. The Poisson regression method is often employed for the statistical analysis of such data. However, data that are not actually counts of
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Specification Test for Poisson Regression Models
International Economic Review, 1986The specification of the Poisson model is tested against some general models for the analysis of counted data. The test of Poisson models is considered against negative binomial distribution, general family of discrete distributions based on Pearson's difference equation and series expansion of distributions.
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2018
In the Chap. 4, binary Poisson regressions were assessed of parallel groups with a binary outcome. In the Chap.5, Poisson regressions were used for data with polytomous outcomes. This chapter will address additional models applying Poisson distributions.
Aeilko H. Zwinderman, Ton J. Cleophas
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In the Chap. 4, binary Poisson regressions were assessed of parallel groups with a binary outcome. In the Chap.5, Poisson regressions were used for data with polytomous outcomes. This chapter will address additional models applying Poisson distributions.
Aeilko H. Zwinderman, Ton J. Cleophas
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Poisson Regression for Clustered Data [PDF]
International Statistical Review, 2007 SummaryWe compare five methods for parameter estimation of a Poisson regression model for clustered data:(1)ordinary (naive) Poisson regression (OP), which ignores intracluster correlation,(2)Poisson regression with fixed cluster‐specific intercepts (FI),(3)a generalized estimating equations (GEE) approach with an equi‐correlation matrix,(4)an exact ...
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Overdispersion in poisson regression
1992Investigation of a possible relationship between air quality and human health in the community of Prince George, British Columbia was undertaken after a public opinion poll in 1972 discovered that poor air quality was the number one concern of the residents of Prince George.
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Generalized poisson regression model
Communications in Statistics - Theory and Methods, 1992The generalized Poisson distribution has been found useful in fitting over-dispersed as well as under-dispersed count data. Since a number of models and methods have been proposed for the regression analysis of count data either with under-dispersion or with over-dispersion, we define and study a generalized Poisson regression (GPR) model which is ...
P.C. Consul, Felix Famoye
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Proposed methods in estimating the ridge regression parameter in Poisson regression model
, 2018The Poisson regression model is considered as an important model among the linear logarithm models. It is usually used to model the count dependent variable.
Z. Algamal, Mazin M. Alanaz
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