SPSS® 12.0 Command Syntax Reference

1242 Syntax Reference
Example
DATA LIST FREE/V1 V2 V3.
BEGIN DATA
3 1 1
6 1 1
3 1 3
3 2 2
3 2 2
6 2 2
6 1 3
6 2 2
3 2 2
6 2 1
END DATA.
AUTORECODE V1 /INTO NEWVAR1.
PRINCALS VARIABLES=NEWVAR1 V2(2) V3(3).
• DATA LIST defines three variables, V1, V2, and V3.
• V1 has two levels, coded 3 and 6, V2 has two levels, coded 1 and 2, and V3 has three levels,
coded 1, 2, and 3.
• The AUTORECODE command creates NEWVAR1 containing recoded values of V1. Values
of 3 are recoded to 1 and values of 6 are recoded to 2.
• A maximum value of 2 can then be specified on the PRINCALS VARIABLES subcommand
as the maximum category value for both NEWVAR1 and V2. A maximum value of 3 is
specified for V3.
ANALYSIS Subcommand
ANALYSIS specifies the variables to be used in the computations and the optimal scaling level
used by PRINCALS to quantify each variable or variable list.
• If ANALYSIS is not specified, an ordinal level of optimal scaling is assumed for all variables.
• The specification on ANALYSIS is a variable list and an optional keyword in parentheses
to indicate the optimal scaling level.
• The variables on the variable list must also be specified on the VARIABLES subcommand.
• Variables listed on the VARIABLES subcommand but not on the ANALYSIS subcommand
can still be used to label object scores on the PLOT subcommand.
The following keywords can be specified to indicate the optimal scaling level:
MNOM Multiple nominal. The quantifications can be different for each dimension. When
all variables are multiple nominal, PRINCALS gives the same results as HOMALS.
SNOM Single nominal. PRINCALS gives only one quantification for each category. Objects
in the same category (cases with the same value on a variable) obtain the same
quantification. When DIMENSION=1 and all variables are SNOM, this solution is the
same as that of the first HOMALS dimension.
ORDI Ordinal. This is the default for variables listed without optimal scaling levels and
for all variables if the ANALYSIS subcommand is not used. The order of the
categories of the observed variable is preserved in the quantified variable.