Two‐part test of vaccine effect |
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| Authors: | Zonghui Hu Michael Proschan |
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| Affiliation: | Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, U.S.A. |
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| Abstract: | Vaccine benefit is usually two‐folded: (i) prevent a disease or, failing that, (ii) diminish the severity of a disease. To assess vaccine effect, we propose two adaptive tests. The weighted two‐part test is a combination of two statistics, one on disease incidence and one on disease severity. More weight is given to the statistic with the larger a priori effect size, and the weights are determined to maximize testing power. The randomized test applies to the scenario where the total number of infections is relatively small. It uses information on disease severity to bolster power while preserving disease incidence as the primary interest. Properties of the proposed tests are explored asymptotically and by numerical studies. Although motivated by vaccine studies, the proposed tests apply to any trials that involve both binary and continuous outcomes for evaluating treatment effect. Published 2015. This article is a US Government work and is in the public domain in the USA. |
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| Keywords: | Fisher's exact test Lachenbruch's test local alternative randomization test vaccine |
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