SPSS® 12.0 Command Syntax Reference

812 LOGISTIC REGRESSION
CRITERIA Subcommand
CRITERIA controls the statistical criteria used in building the logistic regression models. The
way in which these criteria are used depends on the method specified on the METHOD subcommand.
The default criteria are noted in the description of each keyword below. Iterations
will stop if the criterion for BCON, LCON, or ITERATE is satisfied.
BCON(value) Change in parameter estimates to terminate iteration. Iteration terminates
when the parameters change by less than the specified value. The default is
0.001. To eliminate this criterion, specify a value of 0.
ITERATE Maximum number of iterations. The default is 20.
LCON(value) Percentage change in the log-likelihood ratio for termination of iterations.
If the log-likelihood decreases by less than the specified value, iteration terminates.
The default is 0, which is equivalent to not using this criterion.
PIN(value) Probability of score statistic for variable entry. The default is 0.05. The larger
the specified probability, the easier it is for a variable to enter the model.
POUT(value) Probability of conditional, Wald, or LR statistic to remove a variable. The
default is 0.1. The larger the specified probability, the easier it is for a variable
to remain in the model.
EPS(value) Epsilon value used for redundancy checking. The specified value must be
less than or equal to 0.05 and greater than or equal to 10 . The default is
. Larger values make it harder for variables to pass the redundancy
check—that is, they are more likely to be removed from the analysis.
12 –
10 8 –
CUT(value) Cutoff value for classification. A case is assigned to a group when the predicted
event probability is greater than or equal to the cutoff value. The
cutoff value affects the value of the dichotomous derived variable in the
classification table, the predicted group (PGROUP on CASEWISE), and the
classification plot (CLASSPLOT). The default cutoff value is 0.5. You can
specify a value between 0 and 1 (0 < value < 1).
Example
LOGISTIC REGRESSION PROMOTED WITH AGE JOBTIME RACE
/CATEGORICAL RACE
/METHOD BSTEP
/CRITERIA BCON(0.01) PIN(0.01) POUT(0.05).
• A backward stepwise logistic regression analysis is performed for the dependent variable
PROMOTED and the independent variables AGE, JOBTIME, and RACE.
• CRITERIA alters four of the statistical criteria that control the building of a model.
• BCON specifies that if the change in the absolute value of all of the parameter estimates
is less than 0.01, the iterative estimation process should stop. Larger values lower the
number of iterations required. Notice that the ITER and LCON criteria remain unchanged
and that if either of them is met before BCON, iterations will terminate. (LCON can be set
to 0 if only BCON and ITER are to be used.)