METHOD Subcommand (COXREG command)
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 afterWITH
on theVARIABLES
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 thanPIN
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 specifiedPOUT
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.BSTEP. Backward stepwise. As a first step, the covariates specified on
BSTEP
are entered into the model together and are tested for removal one by one. Stepwise removal and entry then follow the same process as described forFSTEP
until no more variables meet entry and removal criteria, or when the current model is the same as a previous one. - Multiple
METHOD
subcommands are allowed and are processed in the order in which they are specified. Each method starts with the results from the previous method. IfBSTEP
is used, all eligible variables are entered at the first step. All variables are then eligible for entry and removal unless they have been excluded from theMETHOD
variable list. - The statistic used in the test for removal can be
specified by an additional keyword in parentheses following
FSTEP
orBSTEP
. IfFSTEP
orBSTEP
is specified by itself, the default isCOND
.
COND. Conditional
statistic. This is the default if FSTEP
or BSTEP
is
specified by itself
WALD. Wald statistic. The removal of a covariate from the model is based on the significance of the Wald statistic.
LR. Likelihood
ratio. The removal of a covariate from the model is based
on the significance of the change in the log-likelihood. If LR
is specified, the model must be reestimated
without each of the variables in the model. This can substantially
increase computational time. However, the likelihood-ratio statistic
is better than the Wald statistic for deciding which variables are
to be removed.
Example
COXREG VARIABLES = SURVIVAL WITH GROUP SMOKE DRINK
/STATUS SURVSTA (1)
/CATEGORICAL = GROUP SMOKE DRINK
/METHOD ENTER GROUP
/METHOD BSTEP (LR) SMOKE DRINK SMOKE BY DRINK.
- GROUP, SMOKE, and DRINK are specified as covariates and as categorical variables.
- The first
METHOD
subcommand entersGROUP
into the model. - Variables in the model at the termination of the
first
METHOD
subcommand are included in the model at the beginning of the secondMETHOD
subcommand. - The second
METHOD
subcommand adds SMOKE, DRINK, and the interaction of SMOKE with DRINK to the previous model. - Backward stepwise regression analysis is then done
using the likelihood-ratio statistic as the removal criterion. The
variable GROUP is not eligible
for removal because it was not specified on the
BSTEP
subcommand. - The procedure continues until the removal of a variable
will result in a decrease in the log-likelihood with a probability
smaller than
POUT
.