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
- 对分组且存在删失的寿命表数据，如何检验假定生存曲线的拟合，并减少对删失边际分布的限制。
- 方法与思路
- 作者在给定无删失死亡概率的约束下，估计区间内死亡或删失概率，再构造最大似然拟合检验。
- 材料陈述的贡献
- 摘要称部分既有检验放宽条件后可能失去正确水平，新检验无需限制删失边际分布，但可能损失功效。
- 阅读关注点
- 核对所谓最小条件仍包含哪些要求、分组删失的似然构造，以及检验水平与功效比较的具体设定。
- 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不需要其他条件，摘要未说明完整假设与检验分布。
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.