首页> 外文期刊>Journal of the American Society for Information Science and Technology >Does Research With Statistics Have More Impact? The Citation Rank Advantage of Structural Equation Modeling
【24h】

Does Research With Statistics Have More Impact? The Citation Rank Advantage of Structural Equation Modeling

机译:统计研究会产生更大的影响吗?结构方程建模的引文秩优势

获取原文
获取原文并翻译 | 示例
获取外文期刊封面目录资料

摘要

Statistics are essential to many areas of research and individual statistical techniques may change the ways in which problems are addressed as well as the types of problems that can be tackled. Hence, specific techniques may tend to generate high-impact findings within science. This article estimates the citation advantage of a technique by calculating the average citation rank of articles using it in the issue of the journal in which they were published. Applied to structural equation modeling (SEM) and four related techniques in 3 broad fields, the results show citation advantages that vary by technique and broad field. For example, SEM seems to be more influential in all broad fields than the 4 simpler methods, with one exception, and hence seems to be particularly worth adding to statistical curricula. In contrast, Pearson correlation apparently has the highest average impact in medicine but the least in psychology. In conclusion, the results suggest that the importance of a statistical technique may vary by discipline and that even simple techniques can help to generate high-impact research in some contexts.
机译:统计学对于许多研究领域都是必不可少的,个人统计学技术可能会改变解决问题的方式以及可以解决的问题的类型。因此,特定的技术可能会在科学领域内产生重大影响。本文通过在文章发表的期刊中计算使用该技术的文章的平均引用等级来估算该技术的引用优势。将结果应用于3个广泛领域的结构方程模型(SEM)和4种相关技术,结果显示引文优势因技术和广泛领域而异。例如,除了一种例外,SEM在所有广泛领域似乎都比4种更简单的方法更有影响力,因此似乎特别值得在统计课程中添加。相反,皮尔逊相关性显然在医学上具有最高的平均影响,但在心理学上则具有最小的影响。总之,结果表明统计技术的重要性可能因学科而异,即使是简单的技术也可以在某些情况下帮助产生高影响力的研究。

著录项

  • 来源
  • 作者

    Mike Thelwall; Paul Wilson;

  • 作者单位

    Statistical Cybermetrics Research Group, School of Mathematics and Computer Science, University of Wolverhampton, Wulfruna Street, Wolverhampton WV1 1LY, UK;

    Statistical Cybermetrics Research Group, School of Mathematics and Computer Science, University of Wolverhampton, Wulfruna Street, Wolverhampton WV1 1LY, UK;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号