MODEL Statement
The MODEL statement identifies the variables to be used as the failure time variable, the optional censoring variable, and the explanatory effects, including covariates, main effects, interactions, and nested effects.
The name of the failure time variable precedes the equal sign. This name can optionally be followed by an asterisk, the name of the censoring variable, and a list of censoring values (separated by blanks or commas) enclosed in parentheses.
The censoring variable must be numeric, and the failure time variables must contain nonnegative values. Any observation that has a negative failure time is excluded from the analysis, as is any observation that has a missing value for any of the variables listed in the MODEL statement. Failure time variables in SAS date format are not recommended, because the dates might be translated into negative numbers and consequently the corresponding observations would be discarded.
If the censoring variable takes one of these values, the corresponding failure time is considered to be censored. Following the equal sign are the explanatory effects (sometimes called independent variables or covariates) for the model.
For information about constructing the model effects, see the section Specification and Parameterization of Model Effects in Chapter 3: Shared Concepts.
Table 16.6 summarizes the options available in the MODEL statement. You can specify these options after a slash (/).
Table 16.6: MODEL Statement Options
Option | Description |
|---|
Model Options |
|---|
CLB | Requests confidence limits |
ENTRY= | Specifies the left-truncation time variable |
INCLUDE= | Includes effects in all models for model selection |
INFORMATIVE | Models missing values by using extra indicator variables |
OFFSET= | Specifies the offset variable |
START= | Includes effects in the initial model for model selection |
TYPE3 | Displays the Type 3 or joint tests of effects |
The following list describes these options:
-
CLB
constructs confidence limits for each of the parameter estimates. The confidence level is 0.95 by default; you can change it by specifying the ALPHA= option in the PROC PHSELECT statement.
-
ENTRY=variable
specifies the left-truncation time variable. The left-truncation time is the time at which an individual starts to be observed.
-
INCLUDE=n | single-effect | (effects)
forces effects to be included in all models. If you specify INCLUDE=n, then the first n effects that you list in the MODEL statement are included in all models. If you specify INCLUDE=single-effect or INCLUDE=(effects), then the specified effects are forced into all models. The effects that you specify in this option must be explanatory effects that you specify in the MODEL statement before the slash (/).
-
INFORMATIVE
models missing values by using extra model effects. These effects consist of dummy variables that take the value 1 when the value of a continuous model variable involved in the effect is missing, and take the value 0 otherwise. The missing value in the original model effect is replaced by the average value of the effect for the nonmissing values. For continuous-by-class effects, such as A*x, where A is a classification variable and x is a continuous variable, informative missingness creates multiple dummy columns and substitutes the effect mean of x that corresponds to the respective level of A. Missing values for classification variables are treated as valid levels. For more information about informative missingness, see the section Informative Missingness in Chapter 3: Shared Concepts.
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OFFSET=variable
specifies a variable to be used as an offset to the linear predictor. An offset plays the role of an effect whose coefficient is known to be 1. The offset variable cannot appear in the CLASS statement or elsewhere in the MODEL statement. Observations that have missing values for the offset variable are excluded from the analysis.
-
START=n | single-effect | (effects)
begins the selection process from the designated initial model for the forward and stepwise selection methods. If you specify START=n, then the starting model includes the first n effects that you list in the MODEL statement. If you specify START=single-effect or START=(effects), then the starting model includes those specified effects. The effects that you specify in the START= option must be explanatory effects that you specify in the MODEL statement before the slash (/). This option is not available when you specify METHOD=BACKWARD in the SELECTION statement.
-
TYPE3
requests that Wald statistics for Type 3 contrasts be computed for each effect that you specify in the MODEL statement. For more information, see the section Joint Tests and Type 3 Tests.