Hierarchical modeling of sequential behavioral data: an empirical Bayesian approach.

Getachew A. Dagne*, C. Hendricks Brown, George W. Howe, Bengt O. Muthén

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


The authors review the common methods for measuring strength of contingency between 2 behaviors in a behavioral sequence, the binomial z score and the adjusted cell residual, and point out a number of limitations of these approaches. They present a new approach using log odds ratios and empirical Bayes estimation in the context of hierarchical modeling, an approach not constrained by these limitations. A series of hierarchical models is presented to test the stationarity of behavioral sequences, the homogeneity of sequences across a sample of episodes, and whether covariates can account for variation in sequences across the sample. These models are applied to observational data taken from a study of the behavioral interactions of 254 couples to illustrate their use.

Original languageEnglish (US)
Pages (from-to)262-280
Number of pages19
JournalPsychological Methods
Issue number2
StatePublished - Jun 1 2002

ASJC Scopus subject areas

  • Psychology (miscellaneous)

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