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A quantal statistical isobologram model to identify joint action for chemical mixtures
Author(s) -
Chen D. G.
Publication year - 2009
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.918
Subject(s) - statistical inference , joint (building) , inference , action (physics) , construct (python library) , statistical model , computer science , simple (philosophy) , econometrics , biological system , statistics , mathematics , artificial intelligence , engineering , physics , architectural engineering , philosophy , epistemology , quantum mechanics , biology , programming language
The isobologram model is a commonly used and powerful graphical and statistical tool for analyzing the joint action for simple chemical mixtures. Substantial research has been done for the quantitative response and the amount of research in the qualitative framework is minuscule. In this paper, isobologram model is proposed to analyze the joint action of chemical mixtures for quantal dose‐response relationship based on the generalized linear model technique to estimate the associated parameters by the maximum likelihood estimation and then to be used to construct the isobologram so that the joint action from the chemicals can be identified both by the isobologram and the statistical inference for interaction parameter. A real dataset is used to illustrate the application of the developed approach. Copyright © 2008 John Wiley & Sons, Ltd.