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Correcting for Genomic Inflation Leads to Loss of Power in Large-Scale Genome-Wide Association Study Meta-Analysis. [PDF]
Genet EpidemiolSingh A +11 more
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Invisible Text Injection and Peer Review by AI Models.
JAMA Netw OpenChoi B +8 more
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Score Tests for Zero-Inflated Poisson Models
Computational Statistics & Data Analysis, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jansakul, N., Hinde, J. P.
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Score tests for zero-inflated double poisson regression models
Acta Mathematicae Applicatae Sinica, English Series, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xie, Feng-Chang +2 more
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Journal of Applied Statistics, 2013
In several cases, count data often have excessive number of zero outcomes. This zero-inflated phenomenon is a specific cause of overdispersion, and zero-inflated Poisson regression model (ZIP) has been proposed for accommodating zero-inflated data. However, if the data continue to suggest additional overdispersion, zero-inflated negative binomial (ZINB)
Hossein Zamani, Noriszura Ismail
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In several cases, count data often have excessive number of zero outcomes. This zero-inflated phenomenon is a specific cause of overdispersion, and zero-inflated Poisson regression model (ZIP) has been proposed for accommodating zero-inflated data. However, if the data continue to suggest additional overdispersion, zero-inflated negative binomial (ZINB)
Hossein Zamani, Noriszura Ismail
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A robust score test of homogeneity for zero-inflated count data
Statistical Methods in Medical Research, 2020In many applications of zero-inflated models, score tests are often used to evaluate whether the population heterogeneity as implied by these models is consistent with the data. The most frequently cited justification for using score tests is that they only require estimation under the null hypothesis.
Wei-Wen Hsu +4 more
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Sensitivity of score tests for zero‐inflation in count data
Statistics in Medicine, 2004AbstractIn many biomedical applications, count data have a large proportion of zeros and the zero‐inflated Poisson regression (ZIP) model may be appropriate. A popular score test for zero‐inflation, comparing the ZIP model to a standard Poisson regression model, was given by van den Broek.
Xiang, L, Fung, WK, Lee, AH
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Biometrics, 2001
Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution.
Ridout, Martin +2 more
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Summary. Count data often show a higher incidence of zero counts than would be expected if the data were Poisson distributed. Zero‐inflated Poisson regression models are a useful class of models for such data, but parameter estimates may be seriously biased if the nonzero counts are overdispersed in relation to the Poisson distribution.
Ridout, Martin +2 more
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Weighted Score test based EWMA control charts for Zero-Inflated Poisson Models
Computers & Industrial Engineering, 2021Abstract Zero-inflated Poisson models have been widely used to account for excess zero values in count data. Recent literature pointed out that the quality characteristic could be assumed to depend on a linear function of covariates in zero-inflated Poisson models, which is called risk-adjustment.
Qiuyan Hu, Liu Liu
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