Regression Analysis of Current-Status Data: An Application to Breast-Feeding
当前状态数据的回归分析：母乳喂养应用AI 解读 ↓
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AI 根据所提供的论文材料归类：摘要研究当前状态生存数据及母乳喂养应用，逻辑回归的出现不足以归入经济学离散选择方向。
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当前状态数据的回归分析：母乳喂养应用
- 研究问题
- 仅观察调查时是否仍在母乳喂养，而非准确停止时间时，如何进行多变量生存回归，并兼顾模型简洁性与灵活性？
- 方法与思路
- 作者比较参数、非参数、半参数和标准曲线方法，在比例优势与比例风险框架下检验，并推荐自然三次样条逻辑回归。
- 材料陈述的贡献
- 摘要称不同模型未明显改变应用结论，并建议用自然三次样条表示随儿童年龄变化的基线对数优势，以平衡简洁与拟合。
- 阅读关注点
- 应核对当前状态数据的观测机制、年龄样条的设定、模型比较标准，以及推荐方法对其他生存分析应用的适用条件。
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- 所给 OpenAlex 索引摘要未注明稿件版本；未提供样本规模、检验结果和观测机制条件，不能推断推荐方法普遍最优。
原文摘要
Current-status data are often collected for use in survival analyses, because this type of data generally is considered to be more reliable than retrospective reports of when an event occurred. Although techniques for calculating mean survival time from current-status data are well known, their use in multiple regression models is somewhat troublesome. Using data on current breast-feeding behavior, this article considers a number of techniques that have been suggested in the literature, including parametric, nonparametric, and semiparametric models as well as the application of standard schedules. Models are tested in both proportional-odds and proportional-hazards frameworks. Although the choice of models does not strongly affect the conclusions that would be drawn, I recommend that a logistic regression in which the baseline log-odds of breast-feeding by child's age are represented by a natural cubic spline should be the preferred methodology. This methodology offers a reasonable compromise between the parsimony of parametric models and the flexibility and good fit of nonparametric models. The same methodology may be well suited to other applications in which there are no theoretical reasons to use a particular parametric form.