On the Reproducibility of Psychological Science
论心理科学的可重复性AI 解读 ↓
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论心理科学的可重复性
- 研究问题
- 心理实验原始研究与重复研究的显著性比例为何差异明显，发表偏差和所检验效应的分布能在多大程度上解释这一现象？
- 方法与思路
- 作者对一百项心理实验的重复研究资料重新建模，将未发表结果视作缺失数据，并同时估计非零效应的分布。
- 材料陈述的贡献
- 摘要称，模型提示合格实验中超过九成检验针对可忽略效应，并将观察到的不可重复现象归因于基于 p 值的发表偏差。
- 阅读关注点
- 应核对发表选择机制、可忽略效应的定义及效应分布设定，并检查模型识别、敏感性分析与提高发现门槛的论证。
- 阅读边界
- 仅据版本未注明的 OpenAlex 索引摘要；上述解释属于模型推断，不能据此确认发表偏差的因果作用或推广到所有心理研究。
原文摘要
Investigators from a large consortium of scientists recently performed a multi-year study in which they replicated 100 psychology experiments. Although statistically significant results were reported in 97% of the original studies, statistical significance was achieved in only 36% of the replicated studies. This article presents a reanalysis of these data based on a formal statistical model that accounts for publication bias by treating outcomes from unpublished studies as missing data, while simultaneously estimating the distribution of effect sizes for those studies that tested nonnull effects. The resulting model suggests that more than 90% of tests performed in eligible psychology experiments tested negligible effects, and that publication biases based on p-values caused the observed rates of nonreproducibility. The results of this reanalysis provide a compelling argument for both increasing the threshold required for declaring scientific discoveries and for adopting statistical summaries of evidence that account for the high proportion of tested hypotheses that are false. Supplementary materials for this article are available online.