Literature DB >> 2466491

The use of a mixture model in the analysis of count data.

V T Farewell1, D A Sprott.   

Abstract

A mixture model is presented for the analysis of data on premature ventricular contractions. The analysis is shown to be straightforward and the conclusions relatively simple.

Mesh：

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Year:  1988        PMID： 2466491

Source DB:  PubMed          Journal:  Biometrics        ISSN： 0006-341X            Impact factor:   2.571


  6 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.  Marginal mean models for zero-inflated count data.

Authors:  David Todem; KyungMann Kim; Wei-Wen Hsu
Journal:  Biometrics       Date:  2016-02-17       Impact factor: 2.571

3.  On testing for homogeneity with zero-inflated models through the lens of model misspecification.

Authors:  Wei-Wen Hsu; Nadeesha R Mawella; David Todem
Journal:  Int Stat Rev       Date:  2021-07-05       Impact factor: 1.946

4.  A quasi-score statistic for homogeneity testing against covariate-varying heterogeneity.

Authors:  David Todem; Wei-Wen Hsu; Jason P Fine
Journal:  Scand Stat Theory Appl       Date:  2017-12-14       Impact factor: 1.396

5.  Zero inflation in ordinal data: incorporating susceptibility to response through the use of a mixture model.

Authors:  Mary E Kelley; Stewart J Anderson
Journal:  Stat Med       Date:  2008-08-15       Impact factor: 2.373

6.  Differential expression analysis for paired RNA-Seq data.

Authors:  Lisa M Chung; John P Ferguson; Wei Zheng; Feng Qian; Vincent Bruno; Ruth R Montgomery; Hongyu Zhao
Journal:  BMC Bioinformatics       Date:  2013-03-27       Impact factor: 3.169
  6 in total

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