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Practical Tests for Comparing Two Proportions with Incomplete Data

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  • S. C. Choi
  • D. M. Stablein

Abstract

Six simple procedures and the likelihood ratio criterion for testing the equality of two binomial proportions with partially incomplete paired data are examined using Monte Carlo methods. The results suggest that the size of each test is more or less satisfactory for nominal sample sizes. Tests which discard some of the observations are seen to have inferior power in comparison to those utilizing all observations. Recommendations are made for the various situations.

Suggested Citation

  • S. C. Choi & D. M. Stablein, 1982. "Practical Tests for Comparing Two Proportions with Incomplete Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(3), pages 256-262, November.
    • Handle: RePEc:bla:jorssc:v:31:y:1982:i:3:p:256-262
    DOI: 10.2307/2347999
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    Cited by:

    1. Li, Huiqiong & Tian, Guoliang & Tang, Niansheng & Cao, Hongyuan, 2018. "Assessing non-inferiority for incomplete paired-data under non-ignorable missing mechanism," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 69-81.
    2. Tang, Man-Lai & Wang Ng, Kai & Tian, Guo-Liang & Tan, Ming, 2007. "On improved EM algorithm and confidence interval construction for incomplete rxc tables," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2919-2933, March.
    3. Wei Li & Yunqi Zhang & Niansheng Tang, 2023. "Non-Parametric Non-Inferiority Assessment in a Three-Arm Trial with Non-Ignorable Missing Data," Mathematics, MDPI, vol. 11(1), pages 1-26, January.
    4. Ng, Kai Wang & Tang, Man-Lai & Tan, Ming & Tian, Guo-Liang, 2008. "Grouped Dirichlet distribution: A new tool for incomplete categorical data analysis," Journal of Multivariate Analysis, Elsevier, vol. 99(3), pages 490-509, March.

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