Literature DB >> 16143993

A score test for zero-inflation in correlated count data.

Liming Xiang1, Andy H Lee, Kelvin K W Yau, Geoffrey J McLachlan.   

Abstract

To account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero-inflated Poisson mixed regression models is applicable for accommodating the within-cluster dependence. In this paper, a score test for zero-inflation is developed for assessing correlated count data with excess zeros. The sampling distribution and the power of the test statistic are evaluated by simulation studies. The results show that the test statistic performs satisfactorily under a wide range of conditions. The test procedure is further illustrated using a data set on recurrent urinary tract infections. Copyright 2006 John Wiley & Sons, Ltd.

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Year:  2006        PMID: 16143993     DOI: 10.1002/sim.2308

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

1.  On the efficiency of score tests for homogeneity in two-component parametric models for discrete data.

Authors:  David Todem; Wei-Wen Hsu; KyungMann Kim
Journal:  Biometrics       Date:  2012-02-20       Impact factor: 2.571

2.  A doubly-inflated Poisson regression for correlated count data.

Authors:  Erfan Ghasemi; Alireza Akbarzadeh Baghban; Farid Zayeri; Asma Pourhoseingholi; Seyed Mohammadreza Safavi
Journal:  J Appl Stat       Date:  2020-05-01       Impact factor: 1.416

3.  A score test for assessing the cured proportion in the long-term survivor mixture model.

Authors:  Yun Zhao; Andy H Lee; Kelvin K W Yau; Valerie Burke; Geoffrey J McLachlan
Journal:  Stat Med       Date:  2009-11-30       Impact factor: 2.373

  3 in total

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