Universitat Politècnica de Catalunya. Departament d'Estadística i Investigació Operativa
Universitat Politècnica de Catalunya. ADBD - Anàlisi de Dades Complexes per a les Decisions Empresarials
2019-06-02
This article analyzes the increase in the probability of committing type I and type II errors in assessing the significance of the effects when some properly selected runs have not been carried out and their responses have been estimated from the interactions considered null from scratch. This is done by simulating the responses from known models that represent a wide variety of practical situations that the experimenter will encounter; the responses considered to be missing are then estimated and the significance of the effects is assessed. Through comparison with the parameters of the model, the errors are then identified. To assess the significance of the effects when there are missing values, the Box-Meyer method has been used. The conclusions are that 1 missing value in 8 run designs and up to 3 missing values in 16 run designs experiments can be estimated without hardly any notable increase in the probability of error when assessing the significance of the effects.
Peer Reviewed
Postprint (author's final draft)
Article
English
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica; Missing observations (Statistics); Factorial design; Missing values; Negligible interactions; Lenth method; Significant effects.; Dades no observades (Estadística)
https://onlinelibrary.wiley.com/journal/10991638
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Open Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
E-prints [73026]