一个后实证主义者的回应。第2部分:用R演示在PLS和LISREL中启用复制的重要性

IF 2.8 4区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
D. Gefen
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引用次数: 2

摘要

在第一部分中,论证了实证主义的核心原则,即允许证伪,特别是数据,或至少相关或协方差矩阵,应该公开,以便其他人可以尝试证伪至少统计分析。这样做可以提供一个表面上的方向,可能构成科学知识完整性的理想的实证主义方面:提出你的主张,把你的数据放在公共领域,这样别人就可以把它的命题进行测试,并试图证伪或改进它们。第2部分说明了这种披露的重要性。演示首先在PLS和CBSEM R包中复制结构方程建模和回归:研究实践指南(Gefen等人,2000)中的模型,产生与原始论文相同的结果。为了说明需要将数据置于公共领域,然后在相同的数据上运行一组指定不正确的模型。如果数据无法用于测试替代模型,那么PLS和CBSEM都会收敛并产生可信的结果,如果没有提供这样的相关或协方差矩阵,则可能会蒙蔽读者的眼睛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Post-Positivist Answering Back.: Part 2: A Demo in R of the Importance of Enabling Replication in PLS and LISREL
In Part 1 the argument was made for the core Positivist principle of enabling falsification, specifically that data, or at least correlation or covariance matrices, should be made public so that others can attempt to falsify at least the statistical analyses. Doing so could provide a semblance of the direction of what might constitute the desired Positivist aspects of intellectual integrity in science: making your claims and putting your data in the public domain so others may put its propositions to the test and try to falsify or improve on them. Part 2 demonstrates the importance of such disclosure. The demo begins with replicating the model in Structural Equation Modeling and Regression: Guidelines for Research Practice (Gefen et al., 2000) in PLS and CBSEM R packages, producing equivalent results as the original paper. Showing the point about the need to have the data in the public domain, a set of incorrectly specified models on the same data are then run. Both PLS and CBSEM converge and produce plausibly believable results if the data were not available to test alternative models, opening the possibility of pulling the wool over readers' eyes if such a correlation or covariance matrix is not provided.
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来源期刊
Data Base for Advances in Information Systems
Data Base for Advances in Information Systems INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.60
自引率
7.10%
发文量
18
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