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Stepwise procedures for the identification of minimum effective dose with unknown variances

Author

Listed:
  • Tao, Jian
  • Shi, Ning-Zhong
  • Guo, Jianhua
  • Gao, Wei

Abstract

Hsu and Berger (J. Amer. Statist. Assoc. 50 (1999) 468) proposed a stepwise confidence interval procedure for identifying the minimum effective dose in dose-response studies under homoscedasticity. In practice, homogeneity of variance is often in doubt. In this paper, we extend Hsu and Berger's stepwise confidence interval procedure to the case of heteroscedasticity (i.e., inequality of variances across dosages). In addition, we show that the new procedure can properly control the family-wise error rate. We illustrate our procedure with a real example. Finally, we investigate the performance of our procedure and a step-down test procedure based on Welch's approximate t-test via a simulation study. Our procedure is shown, empirically, to perform similar to Welch's procedure.

Suggested Citation

  • Tao, Jian & Shi, Ning-Zhong & Guo, Jianhua & Gao, Wei, 2002. "Stepwise procedures for the identification of minimum effective dose with unknown variances," Statistics & Probability Letters, Elsevier, vol. 57(2), pages 121-131, April.
  • Handle: RePEc:eee:stapro:v:57:y:2002:i:2:p:121-131
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    References listed on IDEAS

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    1. Shi, Ning-Zhong & Jiang, Hua, 1998. "Maximum Likelihood Estimation of Isotonic Normal Means with Unknown Variances," Journal of Multivariate Analysis, Elsevier, vol. 64(2), pages 183-195, February.
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