Selecting significant effects in factorial designs: Lenth’s method versus the Box-Meyer approach
The Lenth method is conceptually simple and probably the most common approach to analyzing the significance of the effects in factorial designs. Here, we compare it with a Bayesian approach proposed by Box and Meyer and which does not appear in the usual software packages. The comparison is made by...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2019 |
| 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:2117/126950 |
| Acceso en línea: | https://hdl.handle.net/2117/126950 https://dx.doi.org/10.1080/02664763.2018.1548584 |
| Access Level: | acceso abierto |
| Palabra clave: | Mathematical statistics Box-Meyer method Factorial designfour-run experiments Lenth method significant effects Estadística matemàtica Estadística -- Metodologia Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica |
| Sumario: | The Lenth method is conceptually simple and probably the most common approach to analyzing the significance of the effects in factorial designs. Here, we compare it with a Bayesian approach proposed by Box and Meyer and which does not appear in the usual software packages. The comparison is made by simulating the results of 4, 8 and 16 run designs in a set of scenarios that mirror practical situations and analyzing the results provided by both methods. Although the results depend on the number of runs and the scenario considered, the use of the Box and Meyer method generally produces better results. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group. |
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