| Summary: | Several procedures are available for analyzing cross-classified data under the Poisson model. When data suggest the presence of "non-Poisson" variation an alternative model is desirable. Often a negative binomial model is useful as an alternative. In this dissertation methodology for analyzing data under a two-parameter negative binomial model is provided. A conditional likelihood approach is suggested to simplify estimation and inference procedures. Large sample properties of the conditional likelihood approach are derived. Based on simulations these properties are examined for small samples. The suggested methodology is applied to two sets of data from ecological research studies. === Source: Dissertation Abstracts International, Volume: 51-02, Section: B, page: 0832. === Major Professor: Duane Meeter. === Thesis (Ph.D.)--The Florida State University, 1989.
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