These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

144 related articles for article (PubMed ID: 28296567)

  • 1. Flexible parametrization of variance functions for quantal response data derived from counts.
    Chen Y; Hanson T
    J Biopharm Stat; 2017; 27(5):858-868. PubMed ID: 28296567
    [TBL] [Abstract][Full Text] [Related]  

  • 2. [Application of detecting and taking overdispersion into account in Poisson regression model].
    Bouche G; Lepage B; Migeot V; Ingrand P
    Rev Epidemiol Sante Publique; 2009 Aug; 57(4):285-96. PubMed ID: 19540683
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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; 136(3):268-77. PubMed ID: 19913934
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Modelling overdispersion and Markovian features in count data.
    Trocóniz IF; Plan EL; Miller R; Karlsson MO
    J Pharmacokinet Pharmacodyn; 2009 Oct; 36(5):461-77. PubMed ID: 19798550
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sensitivity of test for overdispersion in Poisson regression.
    Xiang L; Lee AH
    Biom J; 2005 Apr; 47(2):167-76. PubMed ID: 16389913
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Quasi-Poisson vs. negative binomial regression: how should we model overdispersed count data?
    Ver Hoef JM; Boveng PL
    Ecology; 2007 Nov; 88(11):2766-72. PubMed ID: 18051645
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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; 34(24):3235-45. PubMed ID: 26078035
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Semiparametric models for multilevel overdispersed count data with extra zeros.
    Mahmoodi M; Moghimbeigi A; Mohammad K; Faradmal J
    Stat Methods Med Res; 2018 Apr; 27(4):1187-1201. PubMed ID: 27389670
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Testing approaches for overdispersion in poisson regression versus the generalized poisson model.
    Yang Z; Hardin JW; Addy CL; Vuong QH
    Biom J; 2007 Aug; 49(4):565-84. PubMed ID: 17638291
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Bayesian analysis of overdispersed chromosome aberration data with the negative binomial model.
    Brame RS; Groer PG
    Radiat Prot Dosimetry; 2002; 102(2):115-9. PubMed ID: 12408487
    [TBL] [Abstract][Full Text] [Related]  

  • 11. A new regression model for overdispersed binomial data accounting for outliers and an excess of zeros.
    Ascari R; Migliorati S
    Stat Med; 2021 Jul; 40(17):3895-3914. PubMed ID: 33960503
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Revisiting dispersion in count data item response theory models: The Conway-Maxwell-Poisson counts model.
    Forthmann B; Gühne D; Doebler P
    Br J Math Stat Psychol; 2020 Nov; 73 Suppl 1():32-50. PubMed ID: 31418457
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Regression analyses of counts and rates: Poisson, overdispersed Poisson, and negative binomial models.
    Gardner W; Mulvey EP; Shaw EC
    Psychol Bull; 1995 Nov; 118(3):392-404. PubMed ID: 7501743
    [TBL] [Abstract][Full Text] [Related]  

  • 14. A score test for overdispersion in zero-inflated poisson mixed regression model.
    Xiang L; Lee AH; Yau KK; McLachlan GJ
    Stat Med; 2007 Mar; 26(7):1608-22. PubMed ID: 16794991
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Testing the odds of inherent vs. observed overdispersion in neural spike counts.
    Taouali W; Benvenuti G; Wallisch P; Chavane F; Perrinet LU
    J Neurophysiol; 2016 Jan; 115(1):434-44. PubMed ID: 26445864
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Local influence measure of zero-inflated generalized Poisson mixture regression models.
    Chen XD; Fu YZ; Wang XR
    Stat Med; 2013 Apr; 32(8):1294-312. PubMed ID: 22903860
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Comparing methods for analyzing overdispersed count data in aquatic toxicology.
    Noe DA; Bailer AJ; Noble RB
    Environ Toxicol Chem; 2010 Jan; 29(1):212-9. PubMed ID: 20821437
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Application of negative binomial modeling for discrete outcomes: a case study in aging research.
    Byers AL; Allore H; Gill TM; Peduzzi PN
    J Clin Epidemiol; 2003 Jun; 56(6):559-64. PubMed ID: 12873651
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Regression models for public health surveillance data: a simulation study.
    Kim H; Kriebel D
    Occup Environ Med; 2009 Nov; 66(11):733-9. PubMed ID: 19687020
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Approaches for dealing with various sources of overdispersion in modeling count data: Scale adjustment versus modeling.
    Payne EH; Hardin JW; Egede LE; Ramakrishnan V; Selassie A; Gebregziabher M
    Stat Methods Med Res; 2017 Aug; 26(4):1802-1823. PubMed ID: 26031359
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.