Using factor analysis to validate the Clance Impostor Phenomenon Scale in sample of science, technology, engineering and mathematics doctoral students
Using factor analysis to validate the Clance Impostor Phenomenon Scale in sample of science, technology, engineering and mathematics doctoral students
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利用因子分析在科学、技术、工程和数学博士生样本中验证克兰斯冒充者现象量表
DOI：
10.1016/j.paid.2017.09.039
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发表时间：
2018
影响因子：
4.3
通讯作者：
Youn
中科院分区：
文献类型：
--
作者：
Marsha Simon;Youn
本研究探讨Clance冒名顶替现象量表（CIPS）的因子结构。以前的研究人员在分析仪器时确定了不同的因素结构。有些人得出结论，它包含一个因素;其他人确定了一个两因素的解决方案，而其他研究人员，包括调查的开发者，肯定了一个三因素的结构。本研究采用验证性因素分析（CFA）的方法，利用现有文献中研究者提出的三个模型对量表的因素结构进行了检验。验证性因素分析显示，具有相关残差的单因素模型是更简约的模型。基于这些发现，可以得出结论，单因素模型最适合研究中的数据。
This study examined the factor structure of the Clance Impostor Phenomenon Scale (CIPS). Previous researchers identified different factor structures when analyzing the instrument. Some have concluded that it contains one factor; others identified a two-factor solution while other researchers including the developers of the survey affirm a three-factor structure. This study used confirmatory factor analysis (CFA) to test the factor structure of the instrument using the three models proposed by researchers in the existing literature. The CFA revealed that a one-factor model with correlated residuals was the more parsimonious model. Based on these findings it can be concluded that a single factor model best fits the data in the study.
影响因子：
7
作者：
Flora, DB;Curran, PJ
通讯作者：
Curran, PJ