An application of the clumped binomial model to the analysis of clustered attribute data.

This paper is concerned with the statistical analysis of situations where the experimental units are clusters of subjects, each of whom is classified with respect to the presence of a particular (binary response) attribute. For this purpose, the clumped binomial probability model is used to define an underlying mean rate parameter in terms of which the effects of certain treatments as well as cluster size itself can be investigated. The resulting methodology involves a synthesis of certain maximum likelihood and weighted least squares procedures; it is illustrated for a three-dimensional contingency table pertaining to numbers of deaths in litters of baby mice.