{"title":"$statcheck$ 的设计存在缺陷,没有有效的统计结果拼写检查器","authors":"Ingmar Böschen","doi":"arxiv-2408.07948","DOIUrl":null,"url":null,"abstract":"The R package $statcheck$ is designed to extract statistical test results\nfrom text and check the consistency of the reported test statistics and\ncorresponding p-values. Recently, it has also been featured as a spell checker\nfor statistical results, aimed at improving reporting accuracy in scientific\npublications. In this study, I perform a check on $statcheck$ using a\nnon-exhaustive list of 187 simple text strings with arbitrary statistical test\nresults. These strings represent a wide range of textual representations of\nresults including correctly manageable results, non-targeted test statistics,\nvariable reporting styles, and common typos. Since $statcheck$'s detection\nheuristic is tied to a specific set of statistical test results that strictly\nadhere to the American Psychological Association (APA) reporting guidelines, it\nis unable to detect and check any reported result that even slightly deviates\nfrom this narrow style. In practice, $statcheck$ is unlikely to detect many\nstatistical test results reported in the literature. I conclude that the\ncapabilities and usefulness of the $statcheck$ software are very limited and\nthat it should not be used to detect irregularities in results nor as a spell\nchecker for statistical results. Future developments should aim to incorporate\nmore flexible algorithms capable of handling a broader variety of reporting\nstyles, such as those provided by $JATSdecoder$ and Large Language Models,\nwhich show promise in overcoming these limitations but they cannot replace the\ncritical eye of a knowledgeable reader.","PeriodicalId":501215,"journal":{"name":"arXiv - STAT - Computation","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"$statcheck$ is flawed by design and no valid spell checker for statistical results\",\"authors\":\"Ingmar Böschen\",\"doi\":\"arxiv-2408.07948\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The R package $statcheck$ is designed to extract statistical test results\\nfrom text and check the consistency of the reported test statistics and\\ncorresponding p-values. Recently, it has also been featured as a spell checker\\nfor statistical results, aimed at improving reporting accuracy in scientific\\npublications. In this study, I perform a check on $statcheck$ using a\\nnon-exhaustive list of 187 simple text strings with arbitrary statistical test\\nresults. These strings represent a wide range of textual representations of\\nresults including correctly manageable results, non-targeted test statistics,\\nvariable reporting styles, and common typos. Since $statcheck$'s detection\\nheuristic is tied to a specific set of statistical test results that strictly\\nadhere to the American Psychological Association (APA) reporting guidelines, it\\nis unable to detect and check any reported result that even slightly deviates\\nfrom this narrow style. In practice, $statcheck$ is unlikely to detect many\\nstatistical test results reported in the literature. I conclude that the\\ncapabilities and usefulness of the $statcheck$ software are very limited and\\nthat it should not be used to detect irregularities in results nor as a spell\\nchecker for statistical results. Future developments should aim to incorporate\\nmore flexible algorithms capable of handling a broader variety of reporting\\nstyles, such as those provided by $JATSdecoder$ and Large Language Models,\\nwhich show promise in overcoming these limitations but they cannot replace the\\ncritical eye of a knowledgeable reader.\",\"PeriodicalId\":501215,\"journal\":{\"name\":\"arXiv - STAT - Computation\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-08-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - STAT - Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2408.07948\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - STAT - Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.07948","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
R 软件包 $statcheck$ 设计用于从文本中提取统计检验结果,并检查报告的检验统计量和相应 p 值的一致性。最近,它还被用作统计结果的拼写检查工具,旨在提高科学出版物的报告准确性。在本研究中,我使用一个尚未穷尽的 187 个带有任意统计检验结果的简单文本字符串列表对 $statcheck$ 进行了检查。这些字符串代表了各种结果的文字表述,包括可正确管理的结果、非目标测试统计、多变的报告风格和常见错别字。由于$statcheck$的检测启发式与一组严格遵守美国心理学会(APA)报告指南的特定统计检验结果相联系,因此它无法检测和检查任何报告结果,哪怕是与这种狭隘的风格稍有偏差。实际上,$statcheck$ 不可能检测出文献中报告的许多统计检验结果。我的结论是,$statcheck$ 软件的能力和作用非常有限,它既不能用来检测结果中的不规范之处,也不能作为统计结果的拼写检查器。未来的发展应着眼于纳入更灵活的算法,能够处理更广泛的报告风格,例如 $JATSdecoder$ 和 Large Language Models 提供的算法,它们在克服这些局限性方面显示出前景,但它们无法取代知识渊博的读者的批判性眼光。
$statcheck$ is flawed by design and no valid spell checker for statistical results
The R package $statcheck$ is designed to extract statistical test results
from text and check the consistency of the reported test statistics and
corresponding p-values. Recently, it has also been featured as a spell checker
for statistical results, aimed at improving reporting accuracy in scientific
publications. In this study, I perform a check on $statcheck$ using a
non-exhaustive list of 187 simple text strings with arbitrary statistical test
results. These strings represent a wide range of textual representations of
results including correctly manageable results, non-targeted test statistics,
variable reporting styles, and common typos. Since $statcheck$'s detection
heuristic is tied to a specific set of statistical test results that strictly
adhere to the American Psychological Association (APA) reporting guidelines, it
is unable to detect and check any reported result that even slightly deviates
from this narrow style. In practice, $statcheck$ is unlikely to detect many
statistical test results reported in the literature. I conclude that the
capabilities and usefulness of the $statcheck$ software are very limited and
that it should not be used to detect irregularities in results nor as a spell
checker for statistical results. Future developments should aim to incorporate
more flexible algorithms capable of handling a broader variety of reporting
styles, such as those provided by $JATSdecoder$ and Large Language Models,
which show promise in overcoming these limitations but they cannot replace the
critical eye of a knowledgeable reader.