The LIFEREG Procedure
- Overview
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Getting Started
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Syntax
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Details
Missing Values Model Specification Computational Method Supported Distributions Predicted Values Confidence Intervals Fit Statistics Probability Plotting INEST= Data Set OUTEST= Data Set XDATA= Data Set Computational Resources Bayesian Analysis Displayed Output for Classical Analysis Displayed Output for Bayesian Analysis ODS Table Names ODS Graphics
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Examples
Motorette Failure Computing Predicted Values for a Tobit Model Overcoming Convergence Problems by Specifying Initial Values Analysis of Arbitrarily Censored Data with Interaction Effects Probability Plotting—Right Censoring Probability Plotting—Arbitrary Censoring Bayesian Analysis of Clinical Trial Data
- References
| Missing Values |
Any observation with missing values for the dependent variable is not used in the model estimation unless it is one and only one of the values in an interval specification. Also, if one of the explanatory variables or the censoring variable is missing, the observation is not used. For any observation to be used in the estimation of a model, only the variables needed in that model have to be nonmissing. Predicted values are computed for all observations with no missing explanatory variable values. If the censoring variable is missing, the CENSORED= variable in the OUT= SAS data set is also missing.