Generalized Estimating Equations Statistics

Model Effects. The following options are available:

  • Analysis type. Specify the type of analysis to produce for testing model effects. Type I analysis is generally appropriate when you have a priori reasons for ordering predictors in the model, while Type III is more generally applicable. Wald or generalized score statistics are computed based upon the selection in the Chi-Square Statistics group.
  • Confidence intervals. Specify a confidence level greater than 50 and less than 100. Wald intervals are always produced regardless of the type of chi-square statistics selected, and are based on the assumption that parameters have an asymptotic normal distribution.
  • Log quasi-likelihood function. This controls the display format of the log quasi-likelihood function. The full function includes an additional term that is constant with respect to the parameter estimates; it has no effect on parameter estimation and is left out of the display in some software products.

Print. The following output is available.

  • Case processing summary. Displays the number and percentage of cases included and excluded from the analysis and the Correlated Data Summary table.
  • Descriptive statistics. Displays descriptive statistics and summary information about the dependent variable, covariates, and factors.
  • Model information. Displays the dataset name, dependent variable or events and trials variables, offset variable, scale weight variable, probability distribution, and link function.
  • Goodness of fit statistics. Displays two extensions of Akaike's Information Criterion for model selection: Quasi-likelihood under the independence model criterion (QIC) for choosing the best correlation structure and another QIC measure for choosing the best subset of predictors.
  • Model summary statistics. Displays model fit tests, including likelihood-ratio statistics for the model fit omnibus test and statistics for the Type I or III contrasts for each effect.
  • Parameter estimates. Displays parameter estimates and corresponding test statistics and confidence intervals. You can optionally display exponentiated parameter estimates in addition to the raw parameter estimates.
  • Covariance matrix for parameter estimates. Displays the estimated parameter covariance matrix.
  • Correlation matrix for parameter estimates. Displays the estimated parameter correlation matrix.
  • Contrast coefficient (L) matrices. Displays contrast coefficients for the default effects and for the estimated marginal means, if requested on the EM Means tab.
  • General estimable function(s). Displays the matrices for generating the contrast coefficient (L) matrices.
  • Iteration history. Displays the iteration history for the parameter estimates and log-likelihood and prints the last evaluation of the gradient vector and the Hessian matrix. The iteration history table displays parameter estimates for every n th iterations beginning with the 0th iteration (the initial estimates), where n is the value of the print interval. If the iteration history is requested, then the last iteration is always displayed regardless of n.
  • Working correlation matrix. Displays the values of the matrix representing the within-subject dependencies. Its structure depends upon the specifications in the Repeated tab.

How To Specify Statistics for Generalized Estimating Equations

This feature requires SPSS® Statistics Standard Edition or the Advanced Statistics Option.

  1. From the menus choose:

    Analyze > Generalized Linear Models > Generalized Estimating Equations...

  2. In the Generalized Estimating Equations dialog box, click Statistics.