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 Custom Tables and Advanced Statistics.

  1. From the menus choose:

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

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