Script for analyses

In September 2016, I received an automatic email from PubPeer (Nuijten, M. B., Hartgerink, C. H. J., van Assen, M. A. L. M., Epskamp, S., & Wicherts, J. M. (2015). The prevalence of statistical reporting errors in psychology (1985-2013). Behavior Research Methods. http://dx.doi.org/10.3758/s13428-015-0664-2) informing me that they were some statistical errors in the article.
The putative wrong p values were related to a post-hoc analysis in the general discussion (meaning that there was no error in the main analyses of the two experiments). However, I decided to re-do all the analyses, to understand the errors. After a bit of archeological work, I found the initial DMDX files and re-ran all the analyses.

The good news are that the inferential analyses led to the same conclusions as described in the paper (including the supposed wrong tests). Phew...
The bad news are that the descriptive statistics are sometimes very different from what is described in the paper. I impute that to the use of different statistical software and to manual errors when preprocessing the data (I was used to process DMDX files manually with Excel) and analyzing the data (I was used to run them with STATISTICA). I'm therefore all the more happy to use R now for both pre-processing and statistical analyses (though it is still possible to make errors obviously).

The script below presents the analyses I re-did, with highlights regarding conclusions.

于2016年9月，我收到了一封来自PubPeer（Nuijten, M. B.，Hartgerink, C. H. J.，van Assen, M. A. L. M.，Epskamp, S.，及Wicherts, J. M.（2015）发表的《心理学中统计报告错误的普遍性（1985-2013）》一文的相关自动邮件。邮件指出，该文章中存在一些统计错误。[原文：The prevalence of statistical reporting errors in psychology (1985-2013)]。这些所谓的错误p值与一般讨论中的事后分析相关（意味着两个实验的主要分析中并无错误）。然而，我决定重新进行所有分析，以便理解这些错误。经过一番考古般的工作，我找到了最初的DMDX文件，并重新进行了所有分析。

喜讯是，推断性分析得出的结论与论文中描述的一致（包括所谓的错误测试）。庆幸之余...

不幸的是，描述性统计有时与论文中描述的内容大相径庭。我推测这可能是由于使用了不同的统计软件以及数据预处理和分析过程中的人为错误（我习惯于使用Excel手动处理DMDX文件，以及使用STATISTICA进行分析）。因此，现在能够使用R进行数据预处理和统计分析让我倍感欣慰（尽管显然仍然可能发生错误）。

下面的脚本展示了我所重新进行的分析，并突出了结论。