Cao Lei
- Associate professor
- Supervisor of Master's Candidates
- Name (Pinyin):Cao Lei
- Date of Birth:1980-04-27
- E-Mail:
- Education Level:Postgraduate (Doctoral)
- Degree:Doctoral degree
- Professional Title:Associate professor
- Alma Mater:东北师范大学
- Teacher College:数学与统计学院
Contact Information
- Email:
- Paper Publications
[SCI外博士]]A STEPWISE CONFIDENCE INTERVAL PROCEDURE UNDER UNKNOWN VARIANCES BASED ON AN ASYMMETRIC LOSS FUNCTION FOR TOXICOLOGICAL EVALUATION
Release time:2022-06-17 Hits:
- Affiliation of Author(s):数学与统计学院
- Teaching and Research Group:数学与统计学院
- Journal:Australian & New Zealand Journal of Statistics
- Funded by:国家自然科学基金项目
- Key Words:family-wise error rate; linear-exponential loss function; minimax confidence interval;safety; toxicity studies.
- Abstract:One of the most important issues in toxicity studies is the identification of the equivalence of treatments with a placebo. Because it is unacceptable to declare non-equivalent treatments to be equivalent, it is important to adopt a reliable statistical method to properly control the family-wise error rate (FWER). In dealing with this issue, it is important to keep in mind that overestimating toxicity equivalence is a more serious error than underestimating toxicity equivalence. Consequently asymmetric loss functions are more appropriate than symmetric loss functions. Recently Tao, Tang & Shi (2010) developed a new procedure based on an asymmetric loss function. However, their procedure is somewhat unsatisfactory because it assumes that the variances of various dose levels are known. This assumption is restrictive for some applications. In this study we propose an improved approach based on asymmetric confidence intervals without the restrictive assumption of known variances. The asymmetry guarantees reliability in the sense that the FWER is well controlled. Although our procedure is developed assuming that the variances of various dose levels are unknown but equal, simulation studies show that our procedure still performs quite well when the variances are unequal.
- First Author:Cao Lei
- Indexed by:Journal paper
- Volume:57
- Issue:1
- Page Number:1
- Translation or Not:no
- Date of Publication:2015-03-30