Statistical Challenges for Studying Replication

J. Schauer
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Abstract

Recent empirical research has questioned the replicability of scientific findings in various fields, including medicine, economics, and psychology. This research has also revealed that there is no clear-cut definition or standard analysis methods for replication. As a result, there has been substantial ambiguity over the proper way to design and analyze replication studies. This talk describes statistical considerations for studying replication, and examines their implications. It identifies some surprising statistical strengths and limitations of previous research, including the use of statistical methods with surprisingly high error rates. It then argues that such issues can be avoided in future efforts by taking into account key statistical considerations in the planning and analysis of replication studies.
研究复制的统计挑战
最近的实证研究对包括医学、经济学和心理学在内的各个领域的科学发现的可重复性提出了质疑。这项研究也揭示了复制没有明确的定义或标准的分析方法。因此,在设计和分析重复性研究的正确方法上存在着实质性的歧义。这个演讲描述了研究复制的统计考虑,并检查了它们的含义。它指出了以前研究的一些令人惊讶的统计优势和局限性,包括使用错误率高得惊人的统计方法。然后它认为,通过在规划和分析重复研究时考虑到关键的统计因素,可以在今后的努力中避免这些问题。
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