Non-Ignorable Non-Response Models for Time-Ordered Categorical Variables

SUMMARY This paper presents an analysis of time-ordered categorical variables with incomplete data. The models allow for either an ignorable or a non-ignorable non-response model and take into account the time ordering of the categorical variables. All the necessary computations can be done with standard statistical software. In addition, we present a Bayesian analysis which uses information from previous years in the priors. The methods are presented in the context of an example, using data from the National Crime Survey. Although this paper deals with two-way tables, the methods are readily extended to higher dimensional tables.