Albert J M
Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA.
Stat Med. 1996;15(21-22):2371-8; discussion 2405-12. doi: 10.1002/(SICI)1097-0258(19961115)15:21<2371::AID-SIM456>3.0.CO;2-B.
In this paper, we discuss the analysis of data from small sample animal studies intended to evaluate HIV vaccine efficacy. The focus is on the chimpanzee model with HIV infection, a binary outcome, of primary interest. The problem becomes that of testing for a difference in independent binomial proportions, but aspects of the study design call into question the use of standard approaches. As sample sizes may be as small as one or two per group in this context, it is tempting to utilize previous data; such usage, however, carries a high price in terms of additional assumptions. We present a test, referred to as the control-conditional test, which conditions on the control data and assumes (in a manner of Bayesian estimation) only vague prior information. Comparisons are made with Fisher's exact test and an exact unconditional test. The control-conditional test is also generalized to allow the analysis of data from a differential dose design.
在本文中，我们讨论了对旨在评估HIV疫苗效力的小样本动物研究数据的分析。重点是感染HIV的黑猩猩模型，这是一个二元结局，是主要关注对象。问题变成了检验独立二项比例差异的问题，但研究设计的一些方面对标准方法的使用提出了质疑。在此背景下，每组样本量可能小至一两个，因此利用先前数据很有吸引力；然而，这种使用在额外假设方面代价高昂。我们提出了一种检验方法，称为对照条件检验，它以对照数据为条件，并（以贝叶斯估计的方式）仅假设模糊的先验信息。将其与费舍尔精确检验和精确无条件检验进行了比较。对照条件检验也进行了推广，以允许分析来自差异剂量设计的数据。
