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Multivariate tests comparing binomial probabilities, with application to safety studies for drugs

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  • Alan Agresti
  • Bernhard Klingenberg

Abstract

Summary. In magazine advertisements for new drugs, it is common to see summary tables that compare the relative frequency of several side‐effects for the drug and for a placebo, based on results from placebo‐controlled clinical trials. The paper summarizes ways to conduct a global test of equality of the population proportions for the drug and the vector of population proportions for the placebo. For multivariate normal responses, the Hotelling T2‐test is a well‐known method for testing equality of a vector of means for two independent samples. The tests in the paper are analogues of this test for vectors of binary responses. The likelihood ratio tests can be computationally intensive or have poor asymptotic performance. Simple quadratic forms comparing the two vectors provide alternative tests. Much better performance results from using a score‐type version with a null‐estimated covariance matrix than from the sample covariance matrix that applies with an ordinary Wald test. For either type of statistic, asymptotic inference is often inadequate, so we also present alternative, exact permutation tests. Follow‐up inferences are also discussed, and our methods are applied to safety data from a phase II clinical trial.

Suggested Citation

  • Alan Agresti & Bernhard Klingenberg, 2005. "Multivariate tests comparing binomial probabilities, with application to safety studies for drugs," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(4), pages 691-706, August.
  • Handle: RePEc:bla:jorssc:v:54:y:2005:i:4:p:691-706
    DOI: 10.1111/j.1467-9876.2005.05437.x
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    Cited by:

    1. Bernhard Klingenberg & Alan Agresti, 2006. "Multivariate Extensions of McNemar's Test," Biometrics, The International Biometric Society, vol. 62(3), pages 921-928, September.
    2. B. Klingenberg & A. Solari & L. Salmaso & F. Pesarin, 2009. "Testing Marginal Homogeneity Against Stochastic Order in Multivariate Ordinal Data," Biometrics, The International Biometric Society, vol. 65(2), pages 452-462, June.
    3. Alan Agresti & Sabrina Giordano & Anna Gottard, 2022. "A Review of Score-Test-Based Inference for Categorical Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(1), pages 31-48, September.
    4. Klingenberg, Bernhard & Satopää, Ville, 2013. "Simultaneous confidence intervals for comparing margins of multivariate binary data," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 87-98.
    5. Eleftheraki, Anastasia G. & Kateri, Maria & Ntzoufras, Ioannis, 2009. "Bayesian analysis of two dependent 22 contingency tables," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2724-2732, May.

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