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A New Generalized Poisson Mixture Model for Bimodal Count Data with Drug Effect: an application to Rodent Brief-Access Taste Aversion Experiments

Sheng, Y; Soto, J; Orlu Gul, M; Cortina-Borja, M; Tuleu, C; Standing, J; (2016) A New Generalized Poisson Mixture Model for Bimodal Count Data with Drug Effect: an application to Rodent Brief-Access Taste Aversion Experiments. CPT: Pharmacometrics & Systems Pharmacology , 5 (8) pp. 427-436. Green open access

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Abstract

Pharmacodynamic count data can exhibit bimodality and non-equidispersion, complicating the inclusion of drug effect. The aim of this study was to explore four different mixture distribution models for bimodal count data by including both drug effect and distribution truncation. An example dataset, which exhibited bimodal pattern, was from rodent brief-access taste aversion (BATA) experiments to assess the bitterness of ascending concentrations of an aversive tasting drug. The two generalized Poisson mixture model performed the best and was flexible to explain both under and over dispersion. A sigmoid E max model with logistic transformation was introduced to link the drug effect to the data partition within each distribution. Predicted density-histogram plot is suggested as a model evaluation tool due to its capability to directly compare the model predicted density with the histogram from raw data. The modeling approach presented here could form a useful strategy for modeling similar count data types.

Type: Article
Title: A New Generalized Poisson Mixture Model for Bimodal Count Data with Drug Effect: an application to Rodent Brief-Access Taste Aversion Experiments
Open access status: An open access version is available from UCL Discovery
Publisher version: http://dx.doi.org/10.1002/psp4.12093
Language: English
Additional information: (C)2016 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Infection, Immunity and Inflammation Dept
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Population, Policy and Practice Dept
URI: https://discovery.ucl.ac.uk/id/eprint/1498819
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