當前在教育以及心理計量等領域上，差異試題功能(differential item functioning, DIF)的評估已成為不可或缺的一部份。研究者對於DIF研究的思維也隨著時代不斷演進，近年來，研究者逐漸開始重視對於DIF成因的探討(Zumbo, 2007)。多層次模式上的交叉分類多層次試題反應模式(cross-classification multilevel item response model, CCMIRT)除了能進行差異層面功能(differential facet functioning, DFF)的檢測之外，由於設定試題為隨機效果，有研究者提出也可將DIF效果設定為隨機效果(Van den Noortgate & De Boeck, 2005)，可在分析上得到更多訊息，其中最大的助益則是可以藉由固定效果的添加而觀察隨機DIF效果的變異情形。
在使用試題特徵探討DIF成因時，可將隨機DIF效果與DFF檢測進行結合，鑒於在實務上經常遭遇同時有數個試題特徵皆與試題難度相關的情況，本研究認為在分析模式中應同時考量數個試題特徵的主要效果。因此本研究提出在CCMIRT模式結合隨機DIF效果下可分析數個試題特徵的模式，同時操弄與DIF檢測有關的情境，以期瞭解各種變項在此架構下對於解釋DIF成因的效能以及可能會產生的影響。

Differential item functioning (DIF) analyses are important in terms of test fairness
and test validaity. As Zumbo (2007) states, “Third Generation DIF” is best characterized by a subtle but extremely important change in how we think of DIF. The matter of wanting to know why DIF occurs is an early sign of the third generation of DIF.
To detect differential facet functioning (DFF) in such a multilevel setting, the cross-classification multilevel item response model (CCMIRT) can be adapted. When the group main effect and item-by-group interaction effects are included in the CCMIRT, the random effects of group over items represent the DIF residual. The CCMIRT can be further extended by adding item characteristics predictors to explain the DIF.
The purpose of this study is to investigate the sources of DIF by using the CCMIRT combining with DFF. In the simulation study, the variable about DIF effect were manipulated to better understand the performance of the CCMIRT. For fitting real test situation, the model including multiple item properties was suggested in this study.

論文審定書 i
謝 辭 ii
摘 要 iii
Abstract iv
目 錄 v
圖 次 vi
表 次 vii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 5
第二章 文獻探討 7
第一節 差異試題功能與檢測方法 7
第二節 差異試題功能成因 11
第三節 多層次試題反應模式 17
第四節 交叉分類多層次試題反應模式 22
第三章 研究方法與設計 28
第一節 研究方法 28
第二節 研究設計 35
第四章 研究結果 41
第一節 DIF與DFF檢測結果 41
第二節 以解釋係數探討DIF效果解釋力 53
第三節 以模式適配度指標掌握DIF解釋模式 57
第五章 結論與建議 61
第一節 結論 61
第二節 後續研究建議 72
參考文獻 74

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