NORMALIZATION Subcommand (ANACOR command)

The NORMALIZATION subcommand specifies one of five methods for normalizing the row and column scores. Only the scores and variances are affected; contributions and profiles are not changed.

The following keywords are available:

CANONICAL. For each dimension, rows are the weighted average of columns divided by the matching singular value, and columns are the weighted average of rows divided by the matching singular value. This is the default if the NORMALIZATION subcommand is not specified. DEFAULT is an alias for CANONICAL. Use this normalization method if you are primarily interested in differences or similarities between variables.

PRINCIPAL. Distances between row points and column points are approximations of chi-square distances. The distances represent the distance between the row or column and its corresponding average row or column profile. Use this normalization method if you want to examine both differences between categories of the row variable and differences between categories of the column variable (but not differences between variables).

RPRINCIPAL. Distances between row points are approximations of chi-square distances. This method maximizes distances between row points. This is useful when you are primarily interested in differences or similarities between categories of the row variable.

CPRINCIPAL. Distances between column points are approximations of chi-square distances. This method maximizes distances between column points. This is useful when you are primarily interested in differences or similarities between categories of the column variable.

The fifth method has no keyword. Instead, any value in the range –2 to +2 is specified after NORMALIZATION. A value of 1 is equal to the RPRINCIPAL method, a value of 0 is equal to CANONICAL, and a value of –1 is equal to the CPRINCIPAL method. The inertia is spread over both row and column scores. This method is useful for interpreting joint plots.