Zero‐inflated Poisson regression with random effects to evaluate an occupational injury prevention programme

By Kelvin K. W. Yau, Andy H. Lee. 2001

195 citations recorded by the source corpus.

Subfields: Radiological and Ultrasound Technology, Safety, Risk, Reliability and Quality, Statistics and Probability

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Citations in the corpus

A Bayesian model for repeated measures zero-inflated count data with application to outpatient psychiatric service use (2010, background): “Hall (2000), Yau and Lee (2001) and Min and Agresti (2005) have proposed various random intercept zero-inflated models.”
Get real in individual participant data (IPD) meta‐analysis: a review of the methodology (2015, unknown): “Several extensions have been described that for instance, allow for data with many zeros by introducing a discrete point mass (hierarchical zero-inflated Poisson regression) (Lee et al., 2006; Yau and Lee, 2001; Hall, 2000).”
What Drives the Swing Voter in Africa (2013, background): “…health and epidemiological studies (e.g., Agrawal, Gefland, and Citron-Pousty 2002; Brown, Pagan, and Rodriguez-Oreggia 2005; Minami et al. 2006; Yau and Lee 2001), but this article seeks to demonstrate the value of a count-model approach for studying voting behavior and more broadly for the…”
Zero‐Inflated Negative Binomial Mixed Regression Modeling of Over‐Dispersed Count Data with Extra Zeros (2003, methodology): “Extension of the ZIP model to incorporate random effects can be found in Hall (2000) and Yau and Lee (2001).”
Modeling Nonnegative Data with Clumping at Zero: A Survey (2002, background): “By contrast, Yau and Lee (2001) proposed adding a pair of uncorrelated normal random eects (bi,ci) for the two components of a hurdle model.”
Marginal models for zero inflated clustered data (2004, methodology): “Hall (2000) extended ZIP and ZIB models to see also the clustered data case by introducing cluster specific random effects into the model (Yau and Lee, 2001).”
On the Use of Zero-Inflated and Hurdle Models for Modeling Vaccine Adverse Event Count Data (2006, background): “Hall ( 2000 ), Yau and Lee ( 2001 ), and Berk and Lachenbruch ( 2002 ) included cluster-specific random effects into their zero-inflated models.”
Random effect models for repeated measures of zero-inflated count data (2005, methodology): “We briefly mention a second example, from Yau and Lee (2001).”
Multilevel zero-inflated negative binomial regression modeling for over-dispersed count data with extra zeros (2008, methodology): “The method was used to study caries prevention in dental epidemiology [2], occupational injury [25], child growth and development [3], and health service research [11].”