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Items: 1 to 20 of 138

1.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

Neelon B, Chang HH, Ling Q, Hastings NS.

Stat Methods Med Res. 2016 Dec;25(6):2558-2576. Epub 2014 Mar 28.

PMID:
24682266
2.

A Spatial Poisson Hurdle Model for Exploring Geographic Variation in Emergency Department Visits.

Neelon B, Ghosh P, Loebs PF.

J R Stat Soc Ser A Stat Soc. 2013 Feb 1;176(2):389-413. Epub 2012 Jun 28.

3.

Marginalized multilevel hurdle and zero-inflated models for overdispersed and correlated count data with excess zeros.

Kassahun W, Neyens T, Molenberghs G, Faes C, Verbeke G.

Stat Med. 2014 Nov 10;33(25):4402-19. doi: 10.1002/sim.6237. Epub 2014 Jun 23.

PMID:
24957791
4.

The LZIP: A Bayesian latent factor model for correlated zero-inflated counts.

Neelon B, Chung D.

Biometrics. 2017 Mar;73(1):185-196. doi: 10.1111/biom.12558. Epub 2016 Jul 5.

PMID:
27378066
5.

On performance of parametric and distribution-free models for zero-inflated and over-dispersed count responses.

Tang W, Lu N, Chen T, Wang W, Gunzler DD, Han Y, Tu XM.

Stat Med. 2015 Oct 30;34(24):3235-45. doi: 10.1002/sim.6560. Epub 2015 Jun 15.

6.

On the use of zero-inflated and hurdle models for modeling vaccine adverse event count data.

Rose CE, Martin SW, Wannemuehler KA, Plikaytis BD.

J Biopharm Stat. 2006;16(4):463-81.

PMID:
16892908
7.

Local influence diagnostics for hierarchical count data models with overdispersion and excess zeros.

Rakhmawati TW, Molenberghs G, Verbeke G, Faes C.

Biom J. 2016 Nov;58(6):1390-1408. doi: 10.1002/bimj.201500162. Epub 2016 Jun 29.

PMID:
27356111
8.

Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.

Moineddin R, Meaney C, Agha M, Zagorski B, Glazier RH.

BMC Emerg Med. 2011 Aug 19;11:13. doi: 10.1186/1471-227X-11-13.

9.

A spatiotemporal quantile regression model for emergency department expenditures.

Neelon B, Li F, Burgette LF, Neelon SE.

Stat Med. 2015 Jul 30;34(17):2559-75. doi: 10.1002/sim.6480. Epub 2015 Mar 17.

PMID:
25782041
10.

Zero adjusted models with applications to analysing helminths count data.

Chipeta MG, Ngwira BM, Simoonga C, Kazembe LN.

BMC Res Notes. 2014 Nov 27;7:856. doi: 10.1186/1756-0500-7-856.

11.

Disease mapping of zero-excessive mesothelioma data in Flanders.

Neyens T, Lawson AB, Kirby RS, Nuyts V, Watjou K, Aregay M, Carroll R, Nawrot TS, Faes C.

Ann Epidemiol. 2017 Jan;27(1):59-66.e3. doi: 10.1016/j.annepidem.2016.10.006. Epub 2016 Nov 1.

PMID:
27908590
12.

Zero-inflated and hurdle models of count data with extra zeros: examples from an HIV-risk reduction intervention trial.

Hu MC, Pavlicova M, Nunes EV.

Am J Drug Alcohol Abuse. 2011 Sep;37(5):367-75. doi: 10.3109/00952990.2011.597280.

13.

Functional linear models for zero-inflated count data with application to modeling hospitalizations in patients on dialysis.

Sentürk D, Dalrymple LS, Nguyen DV.

Stat Med. 2014 Nov 30;33(27):4825-40. doi: 10.1002/sim.6241. Epub 2014 Jun 19.

14.

Zero-inflated spatio-temporal models for disease mapping.

Torabi M.

Biom J. 2017 Feb 10. doi: 10.1002/bimj.201600120. [Epub ahead of print]

PMID:
28187237
15.
16.

Bayesian two-part spatial models for semicontinuous data with application to emergency department expenditures.

Neelon B, Zhu L, Neelon SE.

Biostatistics. 2015 Jul;16(3):465-79. doi: 10.1093/biostatistics/kxu062. Epub 2015 Feb 2.

PMID:
25649743
17.

Count data distributions and their zero-modified equivalents as a framework for modelling microbial data with a relatively high occurrence of zero counts.

Gonzales-Barron U, Kerr M, Sheridan JJ, Butler F.

Int J Food Microbiol. 2010 Jan 1;136(3):268-77. doi: 10.1016/j.ijfoodmicro.2009.10.016. Epub 2009 Oct 28.

PMID:
19913934
18.
19.

The k-ZIG: flexible modeling for zero-inflated counts.

Ghosh S, Gelfand AE, Zhu K, Clark JS.

Biometrics. 2012 Sep;68(3):878-85. doi: 10.1111/j.1541-0420.2011.01729.x. Epub 2012 Feb 20.

PMID:
22348816
20.

Local influence measure of zero-inflated generalized Poisson mixture regression models.

Chen XD, Fu YZ, Wang XR.

Stat Med. 2013 Apr 15;32(8):1294-312. doi: 10.1002/sim.5560. Epub 2012 Aug 17.

PMID:
22903860

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