Abstract
This article discusses the asymptotic optimality of statistical inference for response-adaptive designs, which has ethical advantages over traditional methods for clinical trials. The upper bound of statistical power of asymptotically level α tests is derived and the Wald statistic is shown to be asymptotically optimal in terms of achieving the upper bound of the asymptotic power. The rates of coverage error probability of the confidence interval are proven to depend on the convergence rate of the allocation proportions for non-normally distributed responses. When the response density functions are normal density functions, it is proven that the coverage error probability and type I error rate are of the order n−1. The Canadian Journal of Statistics 46: 458–469; 2018
| Original language | English (US) |
|---|---|
| Pages (from-to) | 458-469 |
| Number of pages | 12 |
| Journal | Canadian Journal of Statistics |
| Volume | 46 |
| Issue number | 3 |
| DOIs | |
| State | Published - Sep 1 2018 |
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Keywords
- Confidence interval
- coverage error probability
- most powerful test
- order of type I error rate
- response adaptive designs
Cite this
Response adaptive designs with asymptotic optimality. / Yi, Yanqing; Li, Xuan.
In: Canadian Journal of Statistics, Vol. 46, No. 3, 01.09.2018, p. 458-469.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Response adaptive designs with asymptotic optimality
AU - Yi, Yanqing
AU - Li, Xuan
PY - 2018/9/1
Y1 - 2018/9/1
N2 - This article discusses the asymptotic optimality of statistical inference for response-adaptive designs, which has ethical advantages over traditional methods for clinical trials. The upper bound of statistical power of asymptotically level α tests is derived and the Wald statistic is shown to be asymptotically optimal in terms of achieving the upper bound of the asymptotic power. The rates of coverage error probability of the confidence interval are proven to depend on the convergence rate of the allocation proportions for non-normally distributed responses. When the response density functions are normal density functions, it is proven that the coverage error probability and type I error rate are of the order n−1. The Canadian Journal of Statistics 46: 458–469; 2018
AB - This article discusses the asymptotic optimality of statistical inference for response-adaptive designs, which has ethical advantages over traditional methods for clinical trials. The upper bound of statistical power of asymptotically level α tests is derived and the Wald statistic is shown to be asymptotically optimal in terms of achieving the upper bound of the asymptotic power. The rates of coverage error probability of the confidence interval are proven to depend on the convergence rate of the allocation proportions for non-normally distributed responses. When the response density functions are normal density functions, it is proven that the coverage error probability and type I error rate are of the order n−1. The Canadian Journal of Statistics 46: 458–469; 2018
KW - Confidence interval
KW - coverage error probability
KW - most powerful test
KW - order of type I error rate
KW - response adaptive designs
UR - http://www.scopus.com/inward/record.url?scp=85052674733&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85052674733&partnerID=8YFLogxK
U2 - 10.1002/cjs.11460
DO - 10.1002/cjs.11460
M3 - Article
AN - SCOPUS:85052674733
VL - 46
SP - 458
EP - 469
JO - Canadian Journal of Statistics
JF - Canadian Journal of Statistics
SN - 0319-5724
IS - 3
ER -