A Goodness-of-Fit Test for One-Sample Life Table Data
单样本寿命表数据的拟合优度检验AI 解读 ↓
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单样本寿命表数据的拟合优度检验
- 研究问题
- 对寿命按区间记录且存在删失的数据，如何检验指定生存曲线，并避免依赖不必要的删失边际分布假设？
- 方法与思路
- 作者在给定无删失死亡概率的条件下，估计区间死亡或删失概率，再以这些极大似然估计构造生存曲线拟合检验。
- 材料陈述的贡献
- 摘要称该检验不要求对删失边际分布作假设，并指出更专门检验的条件被放宽后可能无法保持正确检验大小。
- 阅读关注点
- 核对所谓最小条件、死亡与删失关系仍有哪些限制，以及检验大小的保证和减少删失假设所付出的功效代价。
- 阅读边界
- 仅据 OpenAlex 索引摘要，稿件版本未注明；不限制删失边际分布不等于无需其他删失条件，具体限制和功效损失未说明。
原文摘要
Grouped censored data are common in life testing, medical trials, and other fields. Individuals, subject to a disease, have their lifetimes recorded as belonging to a certain interval. If the individuals are censored or removed before death, then it is only known that their lifetimes were at least as great as the beginning of the interval in which the individuals were censored. A goodness-of-fit problem is to test the agreement of a hypothesized survival curve with the observed data. Several tests have been proposed in the literature that require various assumptions about the censoring distribution. It is shown in this article that if these conditions are relaxed, then the tests may no longer have the stated properties, such as the correct size. To derive a test under minimal conditions, the maximum likelihood estimates of the probability of death or censoring in an interval are found, given that the probability of death in the absence of censoring is a certain quantity. The estimates are used to construct the maximum likelihood test of the fit of the postulated survival curve. The test does not require any assumptions about the censoring marginal distribution. If the assumptions for the more specific tests hold, however, then there may be some loss of power.