| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w23298 |
| 来源ID | Working Paper 23298 |
| Identification of and Correction for Publication Bias | |
| Isaiah Andrews; Maximilian Kasy | |
| 发表日期 | 2017-04-03 |
| 出版年 | 2017 |
| 语种 | 英语 |
| 摘要 | Some empirical results are more likely to be published than others. Such selective publication leads to biased estimates and distorted inference. This paper proposes two approaches for identifying the conditional probability of publication as a function of a study’s results, the first based on systematic replication studies and the second based on meta-studies. For known conditional publication probabilities, we propose median-unbiased estimators and associated confidence sets that correct for selective publication. We apply our methods to recent large-scale replication studies in experimental economics and psychology, and to meta-studies of the effects of minimum wages and de-worming programs. |
| 主题 | Econometrics ; Estimation Methods |
| URL | https://www.nber.org/papers/w23298 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/580972 |
| 推荐引用方式 GB/T 7714 | Isaiah Andrews,Maximilian Kasy. Identification of and Correction for Publication Bias. 2017. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w23298.pdf（761KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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