Alternatively export your SIMS data set raw data to XLStat, SAS Stats, JMP, Camo, etc. Roll your own PCA. Some of these external packages may offer additional advanced options. Many varying types and methods exist for multi-variant, PCA, see JOSS article cited above. Use one or more of the stats programs and execute the statistical methods of your choosing.
Preference Mapping: Principal component analysis (PCA) are multivariate data compression techniques
that allows multiple treatments to be graphically displayed as they are differentiated by multiple variables.
These techniques is often applied to assess how several products were differentiated by several sensory descriptors
Conjoint analysis: Conjoint analysis is a popular marketing research technique that marketers sometimes
use to determine what features a new product should have and how it should be priced.
Conjoint analysis is another group of quantitative consumer tests similar to PCA that can be used to
probe consumer perceptions. The goal is determination of which product attribute(s) are most important.
Multiple techniques include Adaptive Conjoint Analysis (ACA), Choice Based Conjoint Analysis (CBC), and others.
SIMS does not currently automate Conjoint statistical reporting, we recommend start by exporting raw data to SAS, JMP, Camo, etc.
Google: SAS Institute 'Conjoint Analysis Examples' for their 92 page SAS Technical Report R-l 09 Conjoint Analysis Examples.
Various statistical techniques are discussed including Metric conjoint analysis and Nonmetric conjoint analysis.
SIMS webpage with some more information: www.sims2000.com/MultipleFactorConceptTesting.asp