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《一项护理本科毕业生属性量表的 Rasch 和因子分析》。

A Rasch and factor analysis of a Paramedic Graduate Attribute scale.

机构信息

Department of Community Emergency Health and Paramedic Practice, Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia.

出版信息

Eval Health Prof. 2012 Jun;35(2):148-68. doi: 10.1177/0163278711407314. Epub 2011 May 24.

Abstract

This study examined the construct validity of the Paramedic Graduate Attribute scale (PGAS) using factor analysis and Rasch Analysis. A convenience sample was used in the study involving paramedics from all states and territories in Australia. Participants were asked to rate the importance of 47 graduate attribute items. Principal components analysis (PCA) was undertaken on the 47 items followed by Oblique Oblimin rotation. For the Rasch analysis item fit, item invariance and dimensionality were examined. A total of 872 paramedics participated in the study (23% response rate). PCA of the 47 items revealed seven factors with eigenvalues greater than 1, accounting for 40.6% of the total variance. The subsequent Rasch analyses based on the seven factors produced seven misfitting items and confirmed a 7-factor solution. The 7-factor PGAS produced a good fit to the Rasch Model and exhibited good reliability and unidimensionality, offering the Australian paramedic discipline a set of empirically based graduate attributes.

摘要

本研究采用因子分析和 Rasch 分析方法检验了护理本科毕业生属性量表(PGAS)的结构效度。该研究采用方便样本,涉及澳大利亚所有州和地区的护理人员。要求参与者对 47 项毕业生属性项目的重要性进行评分。对 47 个项目进行主成分分析(PCA),然后进行斜交 Oblimin 旋转。对于 Rasch 分析,检查了项目拟合、项目不变性和维度。共有 872 名护理人员参与了这项研究(23%的回复率)。对 47 个项目的 PCA 显示,有 7 个特征值大于 1 的因子,占总方差的 40.6%。随后基于这 7 个因子的 Rasch 分析产生了 7 个不拟合的项目,并证实了 7 因子解。7 因子 PGAS 与 Rasch 模型拟合良好,具有良好的可靠性和单维性,为澳大利亚护理学科提供了一套基于经验的毕业生属性。

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