Tests of Independence, Treatment Heterogeneity Dose-Related Trend with Exchangeable Binary Data
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可交换二元数据的独立性、处理异质性与剂量趋势检验
- 研究问题
- 对簇内可交换的二元反应，如何超越均值和二阶相关，检验独立性、处理异质性以及剂量相关趋势？
- 方法与思路
- 作者用簇内相似反应的联合概率表达假设，通过受约束极大似然构造非参数似然比检验，并给出趋势检验的显著性界。
- 材料陈述的贡献
- 摘要称趋势检验的渐近分布并非恰为卡方分布，但可用卡方分布获得其 p 值上界，并用兔毒理数据展示和比较检验。
- 阅读关注点
- 应核对可交换性含义、联合概率约束、各检验的渐近校准，以及趋势检验的 p 值上界是否导致明显保守性。
- 阅读边界
- 仅据 OpenAlex 索引摘要，稿件版本未注明。摘要未说明处理分配或因果识别条件，也未报告与既有检验比较的具体结果。
原文摘要
Existing methods of testing for treatment effects for clustered binary data include the beta-binomial, quasilikelihood GEE procedures. All of these methods revolve around the mean response and the second-order correlation. However, these two parameters alone do not fully determine the effect of treatment. This article develops nonparametric likelihood ratio procedures to test for independence, heterogeneity dose-related trend in dose—response studies involving exchangeable binary data. The hypotheses of independence, heterogeneity trend are expressed in terms of joint probabilities of similar responses among cluster mates. Constrained maximum likelihood estimates of these probabilities are computed and used to construct test statistics. Unlike the test statistics for independence and heterogeneity, the asymptotic distribution of the likelihood ratio test for trend is not exactly a chi-square. However, an upper bound of its p value is obtained by using a chi-squared distribution. A set of clustered binary data from the Shell Toxicology Laboratory, on the developmental effect of a chemical agent on banded Dutch rabbits, is used to illustrate the various test procedures. The same dataset is used to compare the proposed trend test with some existing trend tests, such as those based on a beta-binomial model, generalized estimating equations survey sampling methods.