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                                       Details for article 13 of 16 found articles
 
 
  Quantile plots for mean effects in the presence of variance effects for 2k-p designs
 
 
Title: Quantile plots for mean effects in the presence of variance effects for 2k-p designs
Author: Grego, John M.
Lewis, James F.
Craney, Trevor A.
Appeared in: Communications in statistics
Paging: Volume 29 (2000) nr. 4 pages 1109-1133
Year: 2000
Contents: In robust parameter design, variance effects and mean effects in a factorial experiment are modelled simultaneously. If variance effects are present in a model, correlations are induced among the naive estimators of the mean effects. A simple normal quantile plot of the mean effects may be misleading because the mean effects are no longer iid under the null hypothesis that they are zero. Adjusted quantiles are computed for the case when one variance effect is significant and examples of 8-run and 16-run fractional factorial designs are examined in detail. We find that the usual normal quantiles are similar to adjusted quantiles for all but the largest and smallest ordered effects for which they are conservative. Graphically, the qualitative difference between the two sets of quantiles is negligible (even in the presence of large variance effects) and we conclude that normal probability plots are robust in the presence of variance effects.
Publisher: Taylor & Francis
Source file: Elektronische Wetenschappelijke Tijdschriften
 
 

                             Details for article 13 of 16 found articles
 
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