User Guide

52
Chapter 4
Log-likelihood Convergence. Convergence is assumed if the absolute change or relative
change in the log-likelihood function is less than the value specified, which must be
non-negative. The criterion is not used if the value specified equals 0.
Parameter Convergence. Convergence is assumed if the maximum absolute change or
maximum relative change in the parameter estimates is less than the value specified,
which must be non-negative. The criterion is not used if the value specified equals 0.
Hessian Convergence. For the Absolute specification, convergence is assumed if a
statistic based on the Hessian is less than the value specified. For the
Relative
specification, convergence is assumed if the statistic is less than the product of the
value specified and the absolute value of the log-likelihood. The criterion is not used if
the value specified equals 0.
Maximum scoring steps. Requests to use the Fisher scoring algorithm up to iteration
number n. Specify a positive integer.
Singularity tolerance. This is the value used as tolerance in checking singularity.
Specify a positive value.
Linear Mixed Models Statistics
Figure 4-6
Linear Mixed Models: Statistics dialog box