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Colonial legacies in eponymous species names: a global network perspective

Bharadwaj A, Pick JL, Lenzner B.
europepmc   +1 more source

On Baseline Conditions for Zero-Inflated Longitudinal Count Data [PDF]

Communications in Statistics - Simulation and Computation, 2013
We describe a mixed-effect hurdle model for zero-inflated longitudinal count data, where a baseline variable is included in the model specification. Association between the count data process and the endogenous baseline variable is modeled through a latent structure, assumed to be dependent across equations.
Antonello Maruotti, Valentina Raponi
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The analysis of zero‐inflated count data: Beyond zero‐inflated Poisson regression.

British Journal of Mathematical and Statistical Psychology, 2011
Infrequent count data in psychological research are commonly modelled using zero‐inflated Poisson regression. This model can be viewed as a latent mixture of an “always‐zero” component and a Poisson component. Hurdle models are an alternative class of two‐component models that are seldom used in psychological research, but clearly separate the zero ...
Loeys, Tom, Moerkerke, Beatrijs, De Smet, Olivia, Buysse, Ann   +3 more
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Semiparametric Analysis of Zero‐Inflated Count Data

Biometrics, 2006
SummaryMedical and public health research often involve the analysis of count data that exhibit a substantially large proportion of zeros, such as the number of heart attacks and the number of days of missed primary activities in a given period. A zero‐inflated Poisson regression model, which hypothesizes a two‐point heterogeneity in the population ...
Lam, KF, Bun Cheung, Y, Xue, H
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Small Area Estimation for Zero-Inflated Data

Communications in Statistics - Simulation and Computation, 2011
The commonly used method of small area estimation (SAE) under a linear mixed model may not be efficient if data contain substantial proportion of zeros than would be expected under standard model assumptions (hereafter zero-inflated data). The authors discuss the SAE for zero-inflated data under a two-part random effects model that account for excess ...
Hukum Chandra, U. C. Sud
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Zero-Inflated Poisson Regression for Longitudinal Data

Communications in Statistics - Simulation and Computation, 2009
Medical and public health research often involve the analysis of repeated or longitudinal count data that exhibit excess zeros such as the number of yearly doctor visits by a group of individuals over a number of years. Zero-inflated Poisson (ZIP) regression models can be used to account for excess zeros in count data.
M. Tariqul Hasan, Gary Sneddon
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Sensitivity of score tests for zero‐inflation in count data

Statistics in Medicine, 2004
AbstractIn 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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Analysis of joint modeling of longitudinal zero-inflated power series and zero-inflated time to event data

Journal of Biopharmaceutical Statistics, 2020
In longitudinal studies measurements are often collected on different types of responses for each individual. These may contain several longitudinally measured responses (such as the CD4 count) and the time at which an event occurs (e.g., HIV, death, or dropout from the study). These outcomes are often separately analyzed. Compared to separate modeling,
Mojtaba, Zeinali Najafabadi, Ehsan, Bahrami Samani, Mojtaba, Ganjali   +2 more
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Extreme Value Prediction for Zero-Inflated Data

2012
Depending on the domain, there may be significant ramifications associated with the occurrence of an extreme event (for e.g., the occurrence of a flood from a climatological perspective). However, due to the relative low occurrence rate of extreme events, the accurate prediction of extreme values is a challenging endeavor.
Fan Xin, Zubin Abraham
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