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研究生:陳政謙
研究生(外文):Cheng-Chien Chen
論文名稱:定錨試題參數在不同估計誤差情境對測驗等化之探討
論文名稱(外文):The Impact of Anchor Item Parameters with Estimating Errors on Test Equating
指導教授:盧宏益盧宏益引用關係
指導教授(外文):Hung-Yi Lu
口試委員:林原宏劉正夫
口試委員(外文):Yuan-Horng LinJeng-Fu Liu
口試日期:2011-05-25
學位類別:碩士
校院名稱:輔仁大學
系所名稱:應用統計學研究所
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:45
中文關鍵詞:測驗等化定錨試題測量誤差
外文關鍵詞:test eguatinganchor itemmeasurement error
相關次數:
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  • 下載下載:8
  • 收藏至我的研究室書目清單書目收藏:1
測驗等化係將兩份測驗分數建立在同一量尺上做比較,而在兩份試卷中放入相同的定錨試題為常用的等化設計。相關文獻指出,若試題參數含有誤差,將導致考生能力估計值產生偏誤。本研究擬探討在不同試題反應模式下,定錨試題不同程度的估計誤差以及不同測驗人數、測驗題數、定錨題數比例對於測驗等化結果造成之影響。研究結果顯示,定錨試題參數估計誤差的大小會直接反應在測驗等化上,其中又以難度參數含有估計誤差時影響較大;而增加測驗題數可以降低等化的偏誤,測驗人數的多寡則影響不大,定錨試題比例為總試題數的20%至30%等化效果最佳。
Test equating is a statistical process to adjust scores on different forms to the same scale. According to the item response theory, while processing test equating, anchor items must be involved in different tests, so that they can be served as a link among these tests. According to related references, an error that occurs during item calibration can affect the capability estimation of the tested. This research discusses that, with different reaction modes towards different items, the anchor items can cause errors under different parameters and levels; and that different amounts of the tested, test items, and anchor items have certain impacts on test equating. The result shows that the level of errors occurred in the anchor items can be directly reflected on the test equating, which has greater impact when the difficulty parameters have estimation errors; and increasing test items can reduce bias during test equating, while the amount of the tested has not much impact, and finally, the equating of the anchor shows the best effect when it takes up to 20% to 30% of test items.
目錄
第壹章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的與問題 2
第貳章 文獻探討 3
第一節 測驗理論 3
第二節 測驗等化的意義與設計 10
第三節 測驗等化的方法 13
第四節 測量誤差 16
第參章 研究方法 17
第一節 研究工具 17
第二節 研究設計 17
第三節 研究步驟 20
第肆章 研究結果與分析 22
第一節 定錨參數含有固定分配誤差對等化之影響 22
第二節 參數範圍不同比例分配誤差對等化之影響 30
第三節 使用逐次停止規則下所可能產生的誤差對等化之影響 38
第伍章 結論與建議 41
第一節 結論 41
第二節 建議 42
參考文獻 43
中文文獻 43
英文文獻 43


參考文獻
中文文獻
王寶墉(1995)。現代測驗理論。台北市: 心理出版社有限公司。
余民寧(1992)。試題反應理論的介紹(七)-- 訊息函數。 研習資訊,9(6),5-9。
余民寧(1993)。試題反應理論的介紹(九)-- 測驗分數的等化(上)。研習資訊,10(2),6-11。
英文文獻
Angoff, W. H. (1971). Scales, norms, and equivalent scores. In R. L. Thorndike(Ed.), Educational measurement (2nd ed.) (pp. 508-600). Washington, DC: American Council on Education.
Angoff, W. H. (1982). Summary and derivation of equating methods used at ETS. In P. W. Holland & D. R. Rubin (Eds), Test equating (pp. 55-79). New York : Academic Press.
Baker, F. B. (1993). EQUATE2.0: A computer program for the characteristic curve method of IRT equating. Applied Psychological Measurement, 17, 20.
Chang, H.-H., & Ying, Z.(1997). Nonlinear Sequential Designs for Logistic Item Response Theory Model with Applications to Computerized Adaptive Tests, The Annals of Statistics, 37, 1466-1488.
Chang, Y. C., & Martinsek, A. T. (1992). Fixed size confidence regions for parameters of a logistic regression model. The Annals of Statistics, 20(4), 1953-1969.
Haebara, T. (1980). Equating logistic ability: Scales by a weighted least squares method. Japanese Psychological Research, 22, 144-149.
Hambleton, R. K., & Swaminathan, H. (1985). Item response theory : Principles and applications. Boston, MA : Kluwer-Nijhoff.
Hambleton, R. K., Swaminathan, H.,& Rogers, H. J. (1991). Fundamentals of item response theory. Newbury Park, CA: Sage.
Kolen, M. J., & Brennan, R. L. (2004). Test equating, scaling, and linking : Methods and practices (2nd ed.). New York : Springer-Verlag.
Lord, F. M. (1952). A theory of test scores. Psychometric Monograph, No.7.
Lord, F. M. (1980). Application of item response theory to practical testing problems. Hillsdale, NJ: Lawrence Erlbaum Associates.
Lord, F. M. (1983). Unbiased Estimation of Ablity Parameters, of Their Variance, and of Their Parallel-Forms Reliability, Psychometrika, 54, 233-245.
Reckase, M. D.(1983). A procedure for decision making using tailored testing. In Weiss, D. J., New horizons in Testing: Latent trait test theory and computerized adaptive testing. (pp.237-255).New York: Academic Press.
Spray, J.A. & Reckase, M. D.(1996). Comparison of SPRT and sequential bayes procedures for classifying examinees into two categories using a computerized test. Journal of Educational and Behavioral Statistics, 21(4), 405-414.
Stefanski, L.A. & Carroll, R.J(1985). Covariate measurement error in logistic regression. Annals of Statistics, 13, 1335-1351.
Stocking, M. L., & Lord, F. M. (1983). Developing a common metric in item response theory. Applied Psychological Measurement, 7, 201-210.

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