A Semiparametric Two-Sample Density Ratio Model With a Change Point.

IF 1.3 3区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Biometrical Journal Pub Date : 2024-12-01 DOI:10.1002/bimj.202300214
Jiahui Feng, Kin Yau Wong, Chun Yin Lee
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Abstract

The logistic regression model for a binary outcome with a continuous covariate can be expressed equivalently as a two-sample density ratio model for the covariate. Utilizing this equivalence, we study a change-point logistic regression model within the corresponding density ratio modeling framework. We investigate estimation and inference methods for the density ratio model and develop maximal score-type tests to detect the presence of a change point. In contrast to existing work, the density ratio modeling framework facilitates the development of a natural Kolmogorov-Smirnov type test to assess the validity of the logistic model assumptions. A simulation study is conducted to evaluate the finite-sample performance of the proposed tests and estimation methods. We illustrate the proposed approach using a mother-to-child HIV-1 transmission data set and an oral cancer data set.

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带变化点的半参数双样本密度比模型
带有连续协变量的二元结果逻辑回归模型可以等价地表示为协变量的双样本密度比模型。利用这一等价关系,我们在相应的密度比模型框架内研究了变化点逻辑回归模型。我们研究了密度比模型的估计和推理方法,并开发了最大得分类型检验来检测变化点的存在。与现有工作不同的是,密度比建模框架有助于开发一种自然的 Kolmogorov-Smirnov 类型检验,以评估逻辑模型假设的有效性。我们进行了一项模拟研究,以评估所提出的检验和估算方法的有限样本性能。我们使用 HIV-1 母婴传播数据集和口腔癌数据集说明了所提出的方法。
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来源期刊
Biometrical Journal
Biometrical Journal 生物-数学与计算生物学
CiteScore
3.20
自引率
5.90%
发文量
119
审稿时长
6-12 weeks
期刊介绍: Biometrical Journal publishes papers on statistical methods and their applications in life sciences including medicine, environmental sciences and agriculture. Methodological developments should be motivated by an interesting and relevant problem from these areas. Ideally the manuscript should include a description of the problem and a section detailing the application of the new methodology to the problem. Case studies, review articles and letters to the editors are also welcome. Papers containing only extensive mathematical theory are not suitable for publication in Biometrical Journal.
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