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General classes of multiple binary regression models in dose finding problems for combination therapies
Author(s) -
Gasparini Mauro
Publication year - 2013
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/j.1467-9876.2012.01054.x
Subject(s) - binary number , regression , parametric statistics , relevance (law) , mathematics , regression analysis , statistics , computer science , medicine , arithmetic , political science , law
Summary. The dose finding problem for single compounds has been generalized to combination therapies and several binary regression models have been proposed in the literature. We propose general tools to evaluate them, in particular dose‐free parameterizations of the risks of toxicity and risk ratio functions and plots. New classes of risk functions are also proposed. They generate low dimensional parametric risk functions which are made available to the researcher and commented on for their clinical relevance.