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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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820 LOGLINEAR<br />

Variable List<br />

The variable list specifies the variables to be included in the model. LOGLINEAR analyzes<br />

two classes of variables: categorical and continuous. Categorical variables are used to define<br />

the cells of the table. Continuous variables are used as cell covariates. Continuous variables<br />

can be specified only after the keyword WITH following the list of categorical variables.<br />

• The list of categorical variables must be specified first. Categorical variables must be<br />

numeric and integer.<br />

• A range must be defined for each categorical variable by specifying, in parentheses after<br />

each variable name, the minimum and maximum values for that variable. Separate the<br />

two values with at least one space or a comma.<br />

• To specify the same range for a list of variables, specify the list of variables followed by<br />

a single range. The range applies to all variables on the list.<br />

• To specify a logit model, use the keyword BY (see “Logit Model” below). A variable list<br />

without the keyword BY generates a general loglinear model.<br />

• Cases with values outside the specified range are excluded from the analysis. Non-integer<br />

values within the range are truncated for the purpose of building the table.<br />

Logit Model<br />

• To segregate the independent (factor) variables from the dependent variables in a logit<br />

model, use the keyword BY. The categorical variables preceding BY are the dependent<br />

variables; the categorical variables following BY are the independent variables.<br />

• A total of 10 categorical variables can be specified. In most cases, one of them is<br />

dependent.<br />

• A DESIGN subcommand should be used to request the desired logit model.<br />

• LOGLINEAR displays an analysis of dispersion and two measures of association: entropy<br />

and concentration. These measures are discussed in Haberman (1982) and can be used to<br />

quantify the magnitude of association among the variables. Both are proportional reduction<br />

in error measures. The entropy statistic is analogous to Theil’s entropy measure,<br />

while the concentration statistic is analogous to Goodman and Kruskal’s tau-b. Both<br />

statistics measure the strength of association between the dependent variable and the<br />

predictor variable set.<br />

Cell Covariates<br />

• Continuous variables can be used as covariates. When used, the covariates must be specified<br />

after the keyword WITH following the list of categorical variables. Ranges are not<br />

specified for the continuous variables.<br />

• A variable cannot be named as both a categorical variable and a cell covariate.

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