跳到正文
收录说明
收录范围
保留计量方法研究、相关统计基础,以及实质涉及计量方法的应用、教程、比较和综述。书评、刊务及明确无关内容不公开;身份或相关性证据不足的记录保留待核,补充可靠材料后可重新判断。
预印本来自 arXiv 计量经济学及相关统计、金融分类和主题检索。主题检索从 2021 年起回补;关注作者追溯更早年份,部分历史文献按已核验编号补录。收录不表示通过同行评审,仍可能遗漏。
本库首次提交范围:2004-06-23 — 2026-10-14。
阅读范围
默认显示本库全部预印本。可选“优先阅读”:至少一位作者同时满足有可核验的本站覆盖期刊正式发表记录,且 OpenAlex 总引用超过 1,000 次。按同一作者身份匹配,两项缺一不可。此筛选提供阅读线索,不作为论文质量判断。
日期与排序
默认按最近修订排序;年份和日期筛选使用首次提交时间。同一 arXiv 编号的修订会合并。仅有月份或年份时,日期区间相交也会纳入。

日期精度:到日 3 篇 · 到月 0 篇 · 到年 0 篇

分类与引用
领域和方法依据题名、摘要初步分类,可人工修正;分类不代表论文质量。引用数采用 OpenAlex 单条关联记录,不合计版本。
更新与 AI 解读
正常题录、可靠摘要与引用同步继续;日、周、月简报按核实的发表与修订日期汇总,历史补录保留在文献库。AI 解读依据可靠摘要或已核实原文片段,已有解读保留供阅读参考;缺少可靠材料的条目保持待解读,浏览页面不会触发生成。
3 篇论文
导出

Comparing randomized trials

随机试验的比较:试验参与效应与效应迁移

Disagreements between randomized trials that address the same causal question pose challenges for the interpretation and synthesis of evidence. We sketch a causal framework for comparing the results of randomized trials that explicitly accommodates the possibility of trial engagement effects. Using counterfactual outcomes defined under joint interventions on treatment assignment and trial-related actions, we compare trial-native treatment effects with the effects transported…

AI 解读阅读原文 ↗BibTeX ↓

Generalizing conditional average treatment effects from nested randomized trials to all trial-eligible individuals

将嵌套随机试验的条件平均处理效应推广至全部符合资格者

Randomized controlled trials often enroll participants whose characteristics differ from those of a target population, which can limit the generalizability of the estimated treatment effects when effect modifiers differ across populations. While existing generalizability methods primarily focus on estimating the average treatment effect (ATE) in the target population, such summaries may obscure important heterogeneity that is relevant for clinical and policy decision-making.…

AI 解读阅读原文 ↗BibTeX ↓

The role of assignment in defining and identifying causal effects in randomized trials

随机试验中分配对因果效应定义与识别的作用

In randomized trials, the per-protocol effect, that is, the effect of being assigned a treatment strategy and receiving treatment according to the assigned strategy, is sometimes thought to reflect the effect of the treatment strategy itself, without intervention on assignment. Here, we argue by example that this is not necessarily the case. We examine a causal structure for a randomized trial where these two causal estimands -- the per-protocol effect and the effect of the…

AI 解读阅读原文 ↗BibTeX ↓