Hierarchical modeling of sequential behavioral data: an empirical Bayesian approach

Psychol Methods. 2002 Jun;7(2):262-80. doi: 10.1037/1082-989x.7.2.262.

Abstract

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.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Bayes Theorem*
  • Humans
  • Models, Psychological*