探索性因素分析
统计
利克特量表
项目分析
比例(比率)
背景(考古学)
索引(排版)
差异(会计)
相关性
心理学
数学
心理测量学
计算机科学
会计
万维网
业务
古生物学
物理
生物
量子力学
几何学
作者
Ümit Çelen,Eren Can Aybek
标识
DOI:10.21449/ijate.1173356
摘要
Item analysis is performed by developers as an integral part of the scale development process. Thus, items are excluded from the scale depending on the item analysis prior to the factor analysis. Existing item discrimination indices are calculated based on correlation, yet items with different response patterns are likely to have a similar item discrimination index. This study proposed a new item discrimination index that can be used in Likert type of scales and examined its effect on factor analysis results. For this purpose, simulative datasets were generated, and items were excluded from the analysis according to the .20, .30 and .35 item discrimination index criteria, and exploratory factor analysis was performed for a single factor. Accordingly, it was found that more variance could be explained by a single factor with fewer items compared to other discrimination indices when the .20 criterion of the slope coefficient was used as suggested in this study. Similar findings were obtained using the .35 criterion with other discrimination indices. In this context, it is recommended to use the slope coefficient as an additional discrimination index calculation method in the scale development process.
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