The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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The Role of Artificial Observations in Testing for the Difference of Proportions in Misclassified Binary Data

  • Received : 2012.05.01
  • Accepted : 2012.06.12
  • Published : 2012.06.30
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Abstract

An Agresti-Coull type test is considered for the difference of binomial proportions in two doubly sampled data subject to false-positive error. The performance of the test is compared with the likelihood-based tests. It is shown that the Agresti-Coull test has many desirable properties in that it can approximate the nominal significance level with compatible power performance.

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References

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Cited by

  1. The Role of Artificial Observations in Misclassified Binary Data with Common False-Positive Error vol.25, pp.4, 2012, https://doi.org/10.5351/KJAS.2012.25.4.697