Hierarchical modeling of sequential behavioral data: an empirical Bayesian approach.
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.
Dagne
Getachew A
GA
Department of Epidemiology and Biostatistics, University of South Florida, Tampa 33612, USA. gdagne@hsc.usf.edu
Howe
George W
GW
Brown
C Hendricks
CH
Muthén
Bengt O
BO
D001499:Bayes Theorem; D006801:Humans; D008960:Models, Psychological