The LIFEREG Procedure
- Overview
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Getting Started
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Syntax
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DetailsMissing ValuesModel SpecificationComputational MethodSupported DistributionsPredicted ValuesConfidence IntervalsFit StatisticsProbability PlottingINEST= Data SetOUTEST= Data SetXDATA= Data SetComputational ResourcesBayesian AnalysisDisplayed Output for Classical AnalysisDisplayed Output for Bayesian AnalysisODS Table NamesODS Graphics
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ExamplesMotorette FailureComputing Predicted Values for a Tobit ModelOvercoming Convergence Problems by Specifying Initial ValuesAnalysis of Arbitrarily Censored Data with Interaction EffectsProbability Plotting—Right CensoringProbability Plotting—Arbitrary CensoringBayesian Analysis of Clinical Trial DataModel Postfitting Analysis
- References
Syntax: LIFEREG Procedure
The following statements are available in the LIFEREG procedure:
PROC LIFEREG
<options> ;
BAYES
<options> ;
BY
variables ;
CLASS
variables ;
ESTIMATE
<'label'> estimate-specification <(divisor=n)>
<, …<'label'> estimate-specification <(divisor=n)>> </ options> ;
EFFECTPLOT
<plot-type <(plot-definition-options)>> </ options> ;
INSET
<keyword-list> </ options> ;
LSMEANS
<model-effects> </ options> ;
LSMESTIMATE
model-effect <'label'> values <(divisor=n)>
<, …<'label'> values <(divisor=n)>> </ options> ;
MODEL
response = <effects> </ options> ;
OUTPUT
<OUT=SAS-data-set> <keyword=name …keyword=name> <options> ;
PROBPLOT
</ options> ;
SLICE
model-effect </ options> ;
STORE
<OUT=>item-store-name </ LABEL='label'> ;
TEST
<model-effects> </ options> ;
WEIGHT
variable ;
The MODEL statement is required; it specifies both the variables that are used in the regression part of the model and the distribution that is used for the error (random) component of the model. Each invocation of the LIFEREG procedure can use only one MODEL statement. If multiple MODEL statements are present, only the last is used. You can specify main effects and interaction terms in the MODEL statement, as in the GLM procedure. You can specify initial values in the MODEL statement or in an INEST= data set. If no initial values are specified, the starting estimates are obtained by ordinary least squares. The CLASS statement determines which explanatory variables are treated as categorical. The WEIGHT statement identifies a variable with values that are used to weight the observations. Observations with zero or negative weights are not used to fit the model, although predicted values can be computed for them. The OUTPUT statement creates an output data set that contains predicted values and residuals.
The ESTIMATE, EFFECTPLOT, LSMEANS, LSMESTIMATE, SLICE, STORE, and TEST statements are common to many procedures. Summary descriptions of functionality and syntax for these statements are also given after the PROC LIFEREG statement in alphabetical order, and full documentation about them is available in Chapter 19: Shared Concepts and Topics.