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Replication data for: On Recoding Ordered Treatments as Binary Indicators

NIAID Data Ecosystem2026-05-01 收录

因果推断方法

变量编码

数据链接：

https://doi.org/10.7910/DVN/HYIDT9 数据链接链接失效反馈

官方服务：

资源简介：

Review of Economics and Statistics: Forthcoming.

应用场景：

创建时间：

2024-04-30

因果推断方法

劳动经济政策评估

The method of difference-in-differences (DID) is widely used to study the causal effect of policy interventions in observational studies. DID employs a before and after comparison of the treated and c

Taylor & Francis Group2023-08-29 更新80

R_hatch success variable explanations.csv

孵化成功率分析

变量编码

contains explanations of variable codes in the 'hatch success' data set.

Figshare2023-03-29 更新60

Penalized Spline of Propensity Methods for Treatment Comparison

因果推断方法

治疗效果评估

Valid causal inference from observational studies requires controlling for confounders. When time-dependent confounders are present that serve as mediators of treatment effects and affect future treat

NIAID Data Ecosystem30

A note on Identification of the Difference-in-discontinuities Design

因果推断方法

断点回归分析

This paper examines the identification of the difference-in-discontinuities design.

ICPSR2024-01-01 更新80

Instrument Validity Tests With Causal Forests

工具变量有效性检验

因果推断方法

Assumptions that are sufficient to identify local average treatment effects (LATEs) generate necessary conditions that allow instrument validity to be refuted. The degree to which instrument validity

NIAID Data Ecosystem30

Replication data for: On Recoding Ordered Treatments as Binary Indicators

资源简介：

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