Statistics in Crosstabulations - Maximum-Likelihood Chi-square

The Maximum-Likelihood Chi-square tests the same hypothesis as the Pearson Chi-square statistic; however, its computation is based on Maximum-Likelihood theory. In practice, the M-L Chi-square is usually very close in magnitude to the Pearson Chi-square statistic. For more details about this statistic refer to Bishop, Fienberg, and Holland (1975), or Fienberg, S. E. (1977); Log-linear Analysis also discusses this statistic in greater detail.

Generalized Linear/Nonlinear Model (GLZ). An alternative way to analyze crosstabulation tables is also provided in the Generalized Linear/Nonlinear Model (GLZ) module. This module is an implementation of the generalized linear model and allows you to compute a standard, stepwise, or best subset multiple regression analysis with categorical (as well as continuous) predictors, and for binomial or multinomial dependent (response) variables (see Link function).