Selecting relevant effects in factorial designs
Industrial contexts tend to be as much or more concerned about the probability of ignoring an effect when its influence on the response is relevant (type II error) than about the probability of considering an effect to be active when in fact it is not (type I error). Here, we present a methodology f...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/343666 |
| Acceso en línea: | https://hdl.handle.net/2117/343666 https://dx.doi.org/10.1002/qre.2702 |
| Access Level: | acceso abierto |
| Palabra clave: | Factorial designs Significant effects Type I and Type II errors Classificació AMS::65 Numerical analysis::65G Error analysis and interval analysis Classificació AMS::60 Probability theory and stochastic processes Àrees temàtiques de la UPC::Matemàtiques i estadística |
| Sumario: | Industrial contexts tend to be as much or more concerned about the probability of ignoring an effect when its influence on the response is relevant (type II error) than about the probability of considering an effect to be active when in fact it is not (type I error). Here, we present a methodology for taking into account both types of error by fixing an effect value that is considered large enough to control the probability of it going unnoticed. In addition, we propose a plot to visualize the results obtained. |
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