Exact Power and Sample-Size Computations for the Cochran-Armitage Trend Test

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Abstract
The Cochran-Armitage test of trend is commonly used to determine if a dose-response relationship exists in a wide variety of biomedical settings including clinical trials, carcinogenicity studies, and toxicological risk assessment. For small, sparse, or unbalanced data sets, one generally adopts the exact version of the Cochran-Armitage test of trend for which numerical algorithms and software are readily available. No corresponding algorithms or software exist for the exact power and sample-size computations that are needed at design time, prior to gathering the data. This paper develops a network algorithm for computing the exact power of the Cochran-Armitage test of trend and applies it to several examples, thereby demonstrating that the corresponding asymptotic power computations can be rather misleading.

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