Abstract

A straightforward approach to computing score and profile likelihood confidence intervals for contingency table parameters is described. The computational approach herein avoids two main limitations of existing methods: (1) Compared with existing methods, this paper's approach is applicable to a much broader class of parameters. (2) Unlike existing methods, this paper's approach is not case-specific and, hence, lends itself to a general, yet very simple, computational algorithm. This paper describes the 'sliding quadratic' computational algorithm and illustrates its use on examples that have not been previously considered in the literature. A small-scale simulation study highlights the advantage of using score and profile likelihood intervals rather than Wald intervals.

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