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SPSS® 12.0 Command Syntax Reference

SPSS® 12.0 Command Syntax Reference

SPSS® 12.0 Command Syntax Reference

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CSDESCRIPTIVES 335<br />

• The set of subpopulations is defined by specifying a single categorical variable, or two or<br />

more categorical variables, separated by the BY keyword, whose values are crossed.<br />

• For example, /SUBPOP TABLE = A defines subpopulations based on the levels of variable<br />

A.<br />

• For example, /SUBPOP TABLE = A BY B defines subpopulations based on crossing the levels<br />

of variables A and B.<br />

• A maximum of 17 variables may be specified.<br />

• Numeric or string variables may be specified.<br />

• All specified variables must be unique.<br />

• Stratification or cluster variables may be specified, but no other plan file variables are allowed<br />

on the SUBPOP subcommand.<br />

• Analysis variables may not be specified on the SUBPOP subcommand.<br />

• The BY keyword is used to separate variables.<br />

The DISPLAY keyword specifies the layout of results for subpopulations.<br />

LAYERED Results for all subpopulations are displayed in the same table. This is the default.<br />

SEPARATE Results for different subpopulations are displayed in different tables.<br />

MISSING Subcommand<br />

The MISSING subcommand specifies how missing values are handled.<br />

• All design variables must have valid data. Cases with invalid data for any design variable<br />

are deleted from the analysis.<br />

The SCOPE keyword specifies which cases are used in the analyses. This specification is<br />

applied to analysis variables but not design variables.<br />

ANALYSIS Each statistic is based on all valid data for the analysis variable(s) used in<br />

computing the statistic. Ratios are computed using all cases with valid data<br />

for both of the specified variables. Statistics for different variables may be<br />

based on different sample sizes. This is the default.<br />

LISTWISE Only cases with valid data for all analysis variables are used in computing any<br />

statistics. Statistics for different variables are always based on the same sample<br />

size.<br />

The CLASSMISSING keyword specifies whether user-missing values are treated as valid.<br />

This specification is applied to categorical design variables (i.e., strata, cluster, and subpopulation<br />

variables) only.<br />

EXCLUDE Exclude user-missing values among the strata, cluster, and subpopulation<br />

variables. This is the default.<br />

INCLUDE Include user-missing values among the strata, cluster, and subpopulation<br />

variables. Treat user-missing values for these variables as valid data.

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