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Estimation of Half‐Life Periods in Nonlinear Data

Mayer, Benjamin ; Peter, Raphael S. Balakrishnan, N. ; Everitt, Brian ; Colton, Theodore ; Teugels, Jozef L. ; Piegorsch, Walter ; Ruggeri, Fabrizio

Wiley StatsRef: Statistics Reference Online, 2018, p.1-7

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Título:
Estimation of Half‐Life Periods in Nonlinear Data
Autor: Mayer, Benjamin ; Peter, Raphael S.
Balakrishnan, N. ; Everitt, Brian ; Colton, Theodore ; Teugels, Jozef L. ; Piegorsch, Walter ; Ruggeri, Fabrizio
Assuntos: Applications ; Statistics in Physical Sciences
É parte de: Wiley StatsRef: Statistics Reference Online, 2018, p.1-7
Descrição: Half‐life periods, that is, the amount of time which passes by until the maximally measured concentration of a specific substance of interest is halved, are standard outcomes, for example, in pharmacological or toxicological examinations. A particular characteristic of such time‐dependent concentration measurements is a nonlinear data pattern. Estimating half‐life periods therefore is a two‐stage process, requiring first the application of complex mathematical models to the data, from which a model‐based estimation of the half‐life time is subsequently derived. This article describes the general proceeding of this two‐stage process and presents the most common mathematical models to be used. Specifically, fractional polynomials and generalized additive models are introduced shortly. Moreover, a numerical approach is presented which enables to find the estimate of interest finally. An example application is given along with some useful notes on available software.
Editor: Chichester, UK: John Wiley & Sons, Ltd
Idioma: Inglês

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