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Selecting significant effects in factorial designs: Lenth’s method versus the Box-Meyer approach Xampeny Solaní, Rafael Grima Cintas, Pedro Tort-Martorell Llabrés, Xavier Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa Universitat Politècnica de Catalunya. ADBD - Anàlisi de Dades Complexes per a les Decisions Empresarials Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica Mathematical statistics Box-Meyer method Factorial designfour-run experiments Lenth method significant effects Estadística matemàtica Estadística -- Metodologia 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. Peer Reviewed Postprint (author's final draft) 2019-06-02 Article Xampeny, R., Grima, P., Tort, X. Selecting significant effects in factorial designs: Lenth’s method versus the Box-Meyer approach. "Journal of applied statistics", 02 Juny 2019, vol. 46, núm.8, p.1404-1416 0266-4763 https://hdl.handle.net/2117/126950 10.1080/02664763.2018.1548584 eng https://www.tandfonline.com/doi/abs/10.1080/02664763.2018.1548584?journalCode=cjas20 http://creativecommons.org/licenses/by-nc-nd/3.0/es/ Open Access Attribution-NonCommercial-NoDerivs 3.0 Spain application/pdf Taylor & Francis