SAS/STAT Software

GEE Procedure

The GEE procedure fits generalized linear models for longitudinal data by using the generalized estimating equations (GEE) estimation method of Liang and Zeger (1986). The GEE method fits a marginal model to longitudinal data and is commonly used to analyze longitudinal data when the population-average effect is of interest. The following are highlights of the GEE procedure's features:

  • perform weighted GEE estimation when there are missing data that are missing at random (MAR)
  • supports the following response variable distributions:
    • binomial
    • gamma
    • inverse Gaussian
    • negative binomial
    • normal
    • Poisson
    • multinomial
  • supports the following link functions:
    • complementary log-log
    • identity
    • log
    • logit
    • probit
    • reciprocal
    • power with exponent -2
  • supports the following correlation structures:
    • first order autoregressive
    • exchangeable
    • independent
    • m-dependent
    • unstructured
    • fixed (user specified)
  • performs alternating logistic regression analysis for ordinal and binary data
  • supports ESTIMATE, LSMEANS, and OUTPUT statements
  • creates a SAS data set that corresponds to any output table
  • automatically creates graphs by using ODS Graphics

For further details see the GEE Procedure