Suppr超能文献

多方面的拉施校准:以自我对话量表为例

Many-faceted Rasch calibration: an example using the Self-Talk Scale.

作者信息

Brinthaupt Thomas M, Kang Minsoo

机构信息

Middle Tennessee State University, Murfreesboro, TN, USA

Middle Tennessee State University, Murfreesboro, TN, USA.

出版信息

Assessment. 2014 Apr;21(2):241-9. doi: 10.1177/1073191112446653. Epub 2012 May 14.

Abstract

The purpose of this study was to demonstrate the application of the many-faceted Rasch model to a personality measure. The authors use the model to calibrate the Self-Talk Scale (STS). Good model-data fit supported the measurement of self-talk frequency in adults as a unidimensional construct. Results also supported the proper functioning of the original five-category STS response format. Because of evidence that different items do not contribute equally to the total score, the authors provide information for converting raw STS total scores into more appropriate logit scores. The methodology and results demonstrate how the Rasch model can provide additional support for the validity of measures. Implications for using the Rasch model for personality assessment in general and for using the STS in particular are discussed.

摘要

本研究的目的是展示多面Rasch模型在一项人格测量中的应用。作者使用该模型对自我对话量表(Self-Talk Scale,STS)进行校准。良好的模型与数据拟合支持将成人自我对话频率作为一个单维结构进行测量。结果还支持了原始五类STS反应格式的正常运作。由于有证据表明不同项目对总分的贡献并不相同,作者提供了将原始STS总分转换为更合适的logit分数的信息。该方法和结果展示了Rasch模型如何能够为测量的有效性提供额外支持。讨论了将Rasch模型用于一般人格评估,特别是使用STS的意义。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验