R Statistics: survey and review of packages for the estimation of Rasch models.

IF 1.6 Q2 EDUCATION, SCIENTIFIC DISCIPLINES International Journal of Medical Education Pub Date : 2022-06-24 DOI:10.5116/ijme.629d.d88f
John M Linacre
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引用次数: 1

Abstract

Abstract: R Statistics is a comprehensive and widely-used suite of packages for statistical operations. From 27 R packages indexed with the word "Rasch", 11 packages capable of Rasch estimation and analysis are identified and critiqued. A commercial Rasch application is included for comparison. Three R data frames are used. A larger and a smaller 0/1 data frame are analyzed with the Dichotomous Rasch Model. A polytomous 0/1/2 data frame is analyzed with the Partial Credit Model. The R packages can all use the same data frame. They are easy to use and mostly fast, though their documentation is generally skimpy. Every package has obvious shortcomings, but the unique features of each package could make them all useful. For general Rasch estimation and fit analysis of dichotomous data, three packages stand out: eRm, TAM and autoRasch. Two packages stand out for polytomous data: TAM and autoRasch.

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R统计:调查和审查包的估计拉什模型。
摘要:R Statistics是一个全面且广泛使用的统计操作软件包套件。从27个以“Rasch”为索引的R包中,确定并批评了11个能够进行Rasch估计和分析的包。一个商业Rasch应用程序包括比较。使用了三个R数据帧。用二分类Rasch模型对较大和较小的0/1数据帧进行了分析。用部分信用模型分析了一个多分的0/1/2数据帧。所有R包都可以使用相同的数据帧。它们很容易使用,而且大多速度很快,尽管它们的文档通常很简短。每个包都有明显的缺点,但每个包的独特功能可以使它们都有用。对于二分类数据的一般Rasch估计和拟合分析,有三个包脱颖而出:eRm, TAM和autoRasch。有两个包在多域数据中脱颖而出:TAM和autoRasch。
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来源期刊
International Journal of Medical Education
International Journal of Medical Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
3.90
自引率
3.20%
发文量
38
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