For the latest version of JMP Help, visit JMP.com/help.

For MFA, a singular value decomposition of the X matrix can be defined as follows:
X is an n x p centered and normalized matrix of sub-tables. In consumer research there are n products and p panelists’ ratings.
Q is a p x q matrix of right singular vectors, which are weighted by the MFA singular values to obtain the loadings on q principal components.
Δ is a q x q diagonal matrix of singular values from the generalized PCA. As with PCA, the magnitude of the squared singular values, or eigenvalues, represent the importance of each principal component in the combined analysis.
P is an n x q matrix of right singular vectors, which are weighted by the MFA singular values to obtain the q principal components of the compromise.
M is the n x n diagonal matrix of mass weights.
A is the p x p diagonal matrix of block or panelist weights.
JMP calculations use N - 1 for mass weight calculations. These calculations affect individual and block partial scores.

Help created on 3/19/2020