  Although anger is an important emotion that underlies much overt aggression
at great social cost, little is known about how to quantify anger or to specify
the relationship between anger and the overt behaviors that express it. This
paper proposes a novel statistical model which provides both a metric for the
intensity of anger and an approach to determining the quantitative relationship
between anger intensity and the specific behaviors that it controls. From
observed angry behaviors, we reconstruct the time course of the latent anger
intensity and the linkage between anger intensity and the probability of each
angry behavior. The data on which this analysis is based consist of observed
tantrums had by 296 children in the Madison WI area during the period
1994--1996. For each tantrum, eight angry behaviors were recorded as occurring
or not within each consecutive 30-second unit. So, the data can be
characterized as a multivariate, binary, longitudinal (MBL) dataset with a
latent variable (anger intensity) involved. Data such as these are common in
biomedical, psychological and other areas of the medical and social sciences.
Thus, the proposed modeling approach has broad applications.
