Finding Significant Effects for Unreplicated Fractional Factorials Using the n Smallest Contrasts

Article

Schneider, Helmut; Kasperski, William J.; Weissfeld, Lisa   (1993, ASQC)   Louisiana State University

Journal of Quality Technology    Vol. 25    No. 1
QICID: 11370    January 1993    pp. 18-27
List $10.00
Member $5.00

FOR A LIMITED TIME, ACCESS TO THIS CONTENT IS FREE!
You will need to be signed in.
New to ASQ? Register here.

Article Abstract

Pooling nonsignificant effects to estimate the experimental error variance is considered unsatisfactory because it leads to an underestimation of the variance. Hence, the t statistic based on this variance estimate is inflated and should be used with caution. Instead, several graphical methods, such as the normal probability plot and the Bayes plot, have been suggested to determine active factors. Here a t test based on a less biased estimate of the experimental error variance is considered. Specifically, one uses the sums of squares associated with the n effects that are smallest in absolute value and treats them as a Type II right censored sample. It is shown that the t statistic based on this new variance estimate is much more reliable than the standard t statistic. Using five data sets, it is shown that this method is robust with respect to the number of chosen effects and results in conclusions similar to those obtained using normal probability plots or Bayes plots.

Keywords

Censored data,Testing,Fractional factorial design


Browse QIC Articles Chronologically:     Previous Article     Next Article

New Search

Featured advertisers





ASQ is a global community of people passionate about quality, who use the tools, their ideas and expertise to make our world work better. ASQ: The Global Voice of Quality.