Han Karen E, Catalano Paul J, Senchaudhuri Pralay, Mehta Cyrus
Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
Biometrics. 2004 Mar;60(1):216-24. doi: 10.1111/j.0006-341X.2004.00152.x.
The neurotoxicity of a substance is often tested using animal bioassays. In the functional observational battery, animals are exposed to a test agent and multiple outcomes are recorded to assess toxicity, using approximately 40 animals measured on up to 30 different items. This design gives rise to a challenging statistical problem: a large number of outcomes for a small sample of subjects. We propose an exact test for multiple binary outcomes, under the assumption that the correlation among these items is equal. This test is based upon an exponential model described by Molenberghs and Ryan (1999, Environmetrics 10, 279-300) and extends the methods developed by Corcoran et al. (2001, Biometrics 57, 941-948) who developed an exact test for exchangeably correlated binary data for groups (clusters) of correlated observations. We present a method that computes an exact p-value testing for a joint dose-response relationship. An estimate of the parameter for dose response is also determined along with its 95% confidence bound. The method is illustrated using data from a neurotoxicity bioassay for the chemical perchlorethylene.
一种物质的神经毒性通常使用动物生物测定法进行测试。在功能观察组合试验中，将动物暴露于受试物，并记录多个结果以评估毒性，大约使用40只动物，测量多达30个不同项目。这种设计产生了一个具有挑战性的统计问题：少量受试对象有大量结果。我们在这些项目之间的相关性相等的假设下，提出了一种针对多个二元结果的精确检验方法。该检验基于Molenberghs和Ryan（1999年，《环境计量学》10, 279 - 300）描述的指数模型，并扩展了Corcoran等人（2001年，《生物统计学》57, 941 - 948）开发的方法，他们为相关观察的组（集群）开发了一种针对可交换相关二元数据的精确检验方法。我们提出了一种计算联合剂量反应关系精确p值检验的方法。还确定了剂量反应参数的估计值及其95%置信区间。使用来自化学物质全氯乙烯神经毒性生物测定的数据说明了该方法。
