O'Quigley J
Department of Mathematics, University of California, San Diego, La Jolla 92093-0112.
Biometrics. 1992 Sep;48(3):853-62.
The problem of point and interval estimation following a Phase I trial, carried out according to the scheme outlined by O'Quigley, Pepe, and Fisher (1990, Biometrics 46, 33-48), is investigated. A reparametrization of the model suggested in this earlier work can be seen to be advantageous in some circumstances. Maximum likelihood estimators, Bayesian estimators, and one-step estimators are considered. The continual reassessment method imposes restrictions on the sample space such that it is not possible for confidence intervals to achieve exact coverage properties, however large a sample is taken. Nonetheless, our simulations, based on a small finite sample of 20, not atypical in studies of this type, indicate that the calculated intervals are useful in most practical cases and achieve coverage very close to nominal levels in a very wide range of situations. The relative merits of the different estimators and their associated confidence intervals, viewed from a frequentist perspective, are discussed.
研究了按照奥奎利、佩佩和费舍尔（1990年，《生物统计学》46卷，33 - 48页）概述的方案进行的I期试验后的点估计和区间估计问题。在某些情况下，可以看出对这项早期工作中提出的模型进行重新参数化是有利的。考虑了最大似然估计量、贝叶斯估计量和一步估计量。连续重新评估方法对样本空间施加了限制，使得无论样本量多大，置信区间都不可能实现精确的覆盖特性。尽管如此，我们基于20个小有限样本（在这类研究中并非不典型）的模拟表明，计算出的区间在大多数实际情况下是有用的，并且在非常广泛的情况下实现的覆盖范围非常接近名义水平。从频率主义的角度讨论了不同估计量及其相关置信区间的相对优点。
