Random Effects in Log-Linear Models

H. M. Hudson*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review


    We conduct a simulation study of a two way layout of Poisson counts whose expectations conform to a log-linear model and whose row effects are sampled from a population. The model can apply to a number of contingency tables exhibiting non-constant relative risk. We evaluate the robustness of a generalization of the mixed model ANOVA F-test (Scheffe [1959]) to the presence of interactions. This test statistic, and its extensions to other log-linear models with random effects, is readily calculated in terms of the output of standard log-linear fitting procedures.

    Original languageEnglish
    Pages (from-to)43-50
    Number of pages8
    JournalJournal of Statistical Computation and Simulation
    Issue number1
    Publication statusPublished - 1983


    • contingency table
    • log-linear models
    • mixed model
    • Monte Carlo method
    • Poisson
    • Random effects
    • relative risk


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