Analysis of a Mixture Experiment - Model Tab
Select the Model tab of the Analysis of a Mixture Experiment dialog to access the options described here.
Linear.
y = b1*x1 + b2*x2 + b3*x3
Quadratic.
y = b1*x1 + b2*x2 + b3*x3 + b12 *x1*x2 + b13 *x1*x3 + b23*x2*x3
Special cubic.
y = b1*x1 + b2*x2 + b3*x3 + b12 *x1*x2 + b13 *x1*x3 + b23*x2*x3 + b123*x1*x2*x3
Full cubic.
y = b1*x1 + b2*x2 + b3*x3 + b12 *x1*x2 + b13 *x1*x3 + b23*x2*x3 + d12*x1*x2*(x1-x2) + d13*x1*x3*(x1-x3) + d23*x2*x3*(x2-x3) + b123*x1*x2*x3
(Note that the dij's are also parameters of the model.)
Because of the recoding of factors involved in the computation of pseudo-components (see the Summary: Estimates, pseudo-components option on the Quick tab or the ANOVA/Effects tab), the confounding of factor effects is different when you analyze the recoded factor settings as compared to the original factor settings. As a consequence, when you pool effects into the error term, then the model based on the original factor values may no longer be equivalent to the model based on the recoded (pseudo-component) factors. You can always compare the mean-square-errors that are reported in the spreadsheet with the Summary: Estimates, pseudo-components option on the Quick tab or the ANOVA/Effects tab and the spreadsheet with the Estimates, original components option on the ANOVA/Effects tab.
Select the Ignore some effects check box or click the Effects to ignore button to display the Customized (Pooled) Error Term dialog box, which contains a list of all higher-order terms in the current model. Highlight the effects that you want to ignore, that is, that you want to pool into the error term.