Experience suggests that estimation of the gamma model with one or both of the parameters fixed is fairly routine. The third approach is to allow both and to vary freely, and be estimated as free parameters. To continue, our experience with some carefully constructed data sets suggests that the model with free and is quite difficult to estimate. We found in most cases that and the slope parameters wandered off to extreme values, and ultimately, it was not possible to obtain convergence of the estimator. 4. time varying covariates.
Operation is otherwise the same as for all other parametric survival models.
When there are covariates on the Rhs , in the preceding becomes x where x is the covariate vector, including ONE . The options for the loglinear survival models are the usual ones for nonlinear models. You may provide your own starting values for the models if you wish. In the exponential model, F equals 1, so you should not include it in the list. You can also set the maximum to 0 to compute a Lagrange multiplier statistic if you provide your own starting values.