Title 



Threelevel equivalentestimation splitplot designs based on subset and supplementary difference set designs
 
Author 



 
Abstract 



In many industrial experiments, complete randomization of the runs is impossible as, often, they involve factors whose levels are hard or costly to change. In such cases, the splitplot design is a costefficient alternative that reduces the number of independent settings of the hardtochange factors. In general, the use of generalized least squares is required for model estimation based on data from splitplot designs. However, the ordinary least squares estimator is equivalent to the generalized least squares estimator for some splitplot designs, including some secondorder splitplot response surface designs. These designs are called equivalentestimation designs. An important consequence of the equivalence is that basic experimental design software can be used for model estimation. This article introduces two new families of equivalentestimation splitplot designs, one based on subset designs and another based on supplementary difference set designs. The resulting designs complement existing catalogs of equivalentestimation designs and allow for a more flexible choice of the number of hardtochange factors, the number of easytochange factors, the number and size of whole plots, and the total sample size. It is shown that many of the newly proposed designs possess good predictive properties when compared to Doptimal splitplot designs.   
Language 



English
 
Source (journal) 



IIE transactions  
Publication 



2013
 
Volume/pages 



45:11(2013), p. 11531165
 
ISI 



000321690500002
 
Full text (Publishers DOI) 


  
Full text (publishers version  intranet only) 


  
