Abstract
AbstractIn the first ENBIS conference in Oslo, Kenett and Steinberg (On the application of bootstrapping in analyzing designed experiments. Proceedings of the 1st Annual Conference on Business and Industrial Statistics, Oslo, Norway, 17–18 September 2001) proposed the application of bootstrapping to the analysis of data derived from moderate size designed experiments. In this paper we present follow‐up work with an emphasis on designed experiments with censored data, heteroscedasticity and constraints related to the structure of the experiment. Our results show clear advantages to bootstrap‐based data analysis, which is both robust and relatively easy to apply. The bootstrap analysis often points to problems in linear model analyses that might easily be overlooked. These findings suggest that bootstrapping can contribute significantly to the design of experiments methodology. Copyright © 2006 John Wiley & Sons, Ltd.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
