Computational Method

The LIFEREG Procedure

Computational Method

By default, the LIFEREG Procedure computes initial values for the parameters using ordinary least squares (OLS) ignoring censoring. This might not be the best set of starting values for a given set of data. For example, if there are extreme values in your data the OLS fit may be excessively influenced by the extreme observations, causing an overflow or convergence problems. See Example 36.3 for one way to deal with convergence problems.

You can specify the INITIAL= option in the MODEL statement to override these starting values. You can also specify the INITIAL=, SCALE=, and SHAPE= options to set initial values of the intercept, scale, and shape parameters.

The rank of the design matrix X is estimated before the model is fit. Columns of X that are judged linearly dependent on other columns have the corresponding parameters set to zero. The test for linear dependence is controlled by the SINGULAR= option in the MODEL statement. Variables are included in the model in the order in which they are listed in the MODEL statement with the nonclass variables included in the model before any class variables.

The log-likelihood function is maximized by means of a ridge-stabilized Newton-Raphson algorithm. The maximized value of the log-likelihood can take positive or negative values, depending on the specified model and the values of the maximum likelihood estimates of the model parameters.

A composite chi-square test statistic is computed for each class variable, testing whether there is any effect from any of the levels of the variable. This statistic is computed as a quadratic form in the appropriate parameter estimates using the corresponding submatrix of the asymptotic covariance matrix estimate. The asymptotic covariance matrix is computed as the inverse of the observed information matrix. Note that if the NOINT option is specified and class variables are used, the first class variable contains a contribution from an intercept term.

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