查詢結果分析
來源資料
相關文獻
- Estimating the Latent Trait from Likert-Type Data: A Comparison of Factor Analysis, Item Response Theory, and Multidimensional Scaling
- 大學考試分發入學制檢定方法之改進
- A Comparative Study of DIMTEST and NOHARM in Detecting the Departure from Unidimensionality
- Exploring the Variables That Influence the Performance of the DIF-free-then-DIF Strategy in Assessing Differential Item Functioning
- 新版「金融人才特質測驗」之發展
- 門診病患對醫院滿意度與重視度之調查以臺灣地區區域醫院為例
- 從海難事件的發生論船員與船舶間互動效能的提昇
- WWW的使用瓶頸因素及使用者區隔探討--以北區大學傳播相關學系學生為例
- Rasch模式概率比法的差異試題功能分析
- Maximum Likelihood Estimation of Factor Analysis Using the ECME Algorithm with Complete and Incomplete Data
頁籤選單縮合
題 名 | Estimating the Latent Trait from Likert-Type Data: A Comparison of Factor Analysis, Item Response Theory, and Multidimensional Scaling |
---|---|
作 者 | 詹志禹; | 書刊名 | 國立政治大學學報 |
卷 期 | 72(上) 民85.05 |
頁 次 | 頁299-320 |
分類號 | 521.32 |
關鍵詞 | 李克特式量表; 潛在特質; 因素分析; 試題反應理論; 多維尺度法; 電腦模擬研究; Likert-type data; Latent trait; Factor analysis; Item response theory; Multidimensional scaling; Monte-carlo study; |
語 文 | 英文(English) |
中文摘要 | 本研究比較三個統計模式從李克特式(Likert-Type)資料中估計單向度潛在特質的 能力,這三個模式是「植基於多序類相關(polychoric correlations)的因素分析」(FA-PL) ,「試題反應理論中的漸變反應模式」(IRT-GRM),以及「加權多維展開法」(WMDU) 。一般常用的方法(SSI)---分派連續性整數給李克特式量尺中的一個反應類別(如「非常同 意」),再將每一題得分加總---則做為比較的基準線。 本研究為電腦模擬研究,操弄了樣本大小、測驗長度,以及試題反應分配的偏態程度等三個 自變項,依變項則為回復潛在特質的真傎的正確性,結果發現:IRT-GRM表現得最好,最不 受偏態的影響;FA-PL只有在試題反應分配為常態時,才能表現與IRT-GRM一樣好,而在試 題反應分配為高度偏態時,甚至表現得比SSI差;最後,WMDU只有在試題反應分配為常態 或輕微偏態時,才能表現得與SSI一樣好。本文也討論了這些發現對模式選擇的涵意。 |
英文摘要 | Three statistical models were compared with one another in terms of the ability to recover a unidimensional latent trait from Likert-type data. They are factor analysis based on polychoric correlations (FA-PL), the graded response model in item response theory (IRT-GRM), and the weighted multidimensional unfolding (WMDU). The common procedure of summing up successive integers assigned to response categories (SSI) served as the base-line procedure. Sample size, test length, and skewness of item response distributions were manipulated in this simulation study. Generally speaking, IRT-GRM performed the best and was most robust against skewness. FA-PL were competitive with IRT-GRM only when item responses were normally distributed. It performed even worse than did SSI when item responses were highly skewed. WMDU might be a rival alternative to SSI only when item responses were normally distributed or moderately skewed and sample size was large for MDU models (e.g., N=100). |
本系統中英文摘要資訊取自各篇刊載內容。