SPSS® 12.0 Command Syntax Reference

300 COXREG
processing. If k rows are entered, the first row is discarded and only the
last k –
1 rows are used as the contrast matrix in the analysis.
INDICATOR(refcat) Indicator variables. Contrasts indicate the presence or absence of
category membership. By default, refcat is the last category (represented
in the contrast matrix as a row of zeros). To omit a category other than the
last, specify the sequence number of the category (which is not necessarily
the same as its value) in parentheses after keyword INDICATOR.
Example
COXREG SURVIVAL WITH GROUP
/STATUS SURVSTA (1)
/STRATA=LOCATION
/CATEGORICAL = GROUP
/CONTRAST(GROUP)=SPECIAL(2 -1 -1
0 1 -1).
• The specification of GROUP on CATEGORICAL replaces the variable with a set of contrast
variables.
• GROUP identifies whether a case is in one of the three treatment groups.
• A SPECIAL type contrast is requested. A three-column, two-row contrast matrix is entered
in parentheses.
METHOD Subcommand
METHOD specifies the order of processing and the manner in which the covariates enter the
model. If no METHOD subcommand is specified, the default method is ENTER.
• The subcommand keyword METHOD can be omitted.
• You can list all covariates to be used for the method on a variable list. If no variable list
is specified, the default is ALL: all covariates named after WITH on the VARIABLES subcommand
are used for the method.
• The keyword BY can be used between two variable names to specify an interaction term.
• Variables specified on CATEGORICAL are replaced by sets of contrast variables. The contrast
variables associated with a categorical variable are entered or removed from the
model together.
Three keywords are available to specify how the model is to be built:
ENTER Forced entry. All variables are entered in a single step. This is the default if the
METHOD subcommand is omitted.
FSTEP Forward stepwise. The covariates specified on FSTEP are tested for entry into the
model one by one based on the significance level of the score statistic. The variable with
the smallest significance less than PIN is entered into the model. After each entry,
variables that are already in the model are tested for possible removal based on the
significance of the Wald statistic, likelihood ratio, or conditional criterion. The variable
with the largest probability greater than the specified POUT value is removed and the
model is reestimated. Variables in the model are then again evaluated for removal.
Once no more variables satisfy the removal criteria, covariates not in the model are
evaluated for entry. Model building stops when no more variables meet entry or
removal criteria, or when the current model is the same as a previous one.