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Rose, C.E., Martin, S.W., Wannemuehler, K.A. and Plikaytis, B.D. (2006) On the Use of Zero-Inflated and Hurdle Models for Modeling Vaccine Adverse Event Count Data. Journal of Biopharmaceutical Statistics, 16, 463-481.
https://doi.org/10.2307/2600534

has been cited by the following article:

• TITLE: Weather Impact on Heat-Related Illness in a Tropical City State, Singapore

  AUTHORS: Hai-Yan Xu, Xiuju Fu, Chin Leong Lim, Stefan Ma, Tian Kuay Lim, Paul Anantharajah Tambyah, Mohd Salahuddin Habibullah, Gary Kee Khoon Lee, Lee Ching Ng, Kee Tai Goh, Rick Siow Mong Goh, Lionel Kim Hock Lee

  KEYWORDS: Distributed Lag Nonlinear Model, Heat-Related Illness, Hurdle Model, Negative Binomial distribution, Weather Factors

  JOURNAL NAME: Atmospheric and Climate Sciences, Vol.8 No.1, January 24, 2018

  ABSTRACT: In this article we propose a novel hurdle negative binomial (HNB) regression combined with a distributed lag nonlinear model (DLNM) to model weather factors’ impact on heat related illness (HRI) in Singapore. AIC criterion is adopted to help select proper combination of weather variables and check their lagged effect as well as nonlinear effect. The process of model selection and validation is demonstrated. It is observed that the predicted occurrence rate is close to the observed one. The proposed combined model can be used to predict HRI cases for mitigating HRI occurrences and provide inputs for related public health policy considering climate change impact.