Literature DB >> 1786327

Mixture models for continuous data in dose-response studies when some animals are unaffected by treatment.

D D Boos1, C Brownie.   

Abstract

A mixture model is described for dose-response studies where measurements on a continuous variable suggest that some animals are not affected by treatment. The model combines a logistic regression on dose for the probability an animal will "respond" to treatment with a linear regression on dose for the mean of the responders. Maximum likelihood estimation via the EM algorithm is described and likelihood ratio tests are used to distinguish between the full model and meaningful reduced-parameter versions. Use of the model is illustrated with three real-data examples.

Mesh:

Year:  1991        PMID: 1786327

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


  7 in total

1.  Population PKPD modelling of the long-term hypoglycaemic effect of gliclazide given as a once-a-day modified release (MR) formulation.

Authors:  N Frey; C Laveille; M Paraire; M Francillard; N H G Holford; Roeline Jochemsen
Journal:  Br J Clin Pharmacol       Date:  2003-02       Impact factor: 4.335

2.  Relating Nanoparticle Properties to Biological Outcomes in Exposure Escalation Experiments.

Authors:  T Patel; D Telesca; C Low-Kam; Zx Ji; Hy Zhang; T Xia; J I Zinc; A E Nel
Journal:  Environmetrics       Date:  2014-02-01       Impact factor: 1.900

3.  A Finite Mixture of Nonlinear Random Coefficient Models for Continuous Repeated Measures Data.

Authors:  Nidhi Kohli; Jeffrey R Harring; Cengiz Zopluoglu
Journal:  Psychometrika       Date:  2015-04-30       Impact factor: 2.500

4.  Recommendations for harmonization of data collection and analysis of developmental neurotoxicity endpoints in regulatory guideline studies: Proceedings of workshops presented at Society of Toxicology and joint Teratology Society and Neurobehavioral Teratology Society meetings.

Authors:  Abby A Li; Larry P Sheets; Kathleen Raffaele; Virginia Moser; Angela Hofstra; Alan Hoberman; Susan L Makris; Robert Garman; Brad Bolon; Wolfgang Kaufmann; Roland Auer; Edmund Lau; Thomas Vidmar; Wayne J Bowers
Journal:  Neurotoxicol Teratol       Date:  2017-07-27       Impact factor: 3.763

5.  The use of mixture models to detect effects of major genes on quantitative characters in a plant breeding experiment.

Authors:  C Jiang; X Pan; M Gu
Journal:  Genetics       Date:  1994-01       Impact factor: 4.562

6.  EM-test for homogeneity in a two-sample problem with a mixture structure.

Authors:  Guanfu Liu; Yuejiao Fu; Jianjun Zhang; Xiaolong Pu; Boying Wang
Journal:  J Appl Stat       Date:  2019-08-08       Impact factor: 1.416

7.  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

  7 in total

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