An Analysis of Unidimensionality and Local Independence with some Items Lacking of Local Independence

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Kamontip Srihaset
Suwimon Tirakanant

Abstract

    The purposes of this study were to investigate index change to detect local independence of items when number of item interaction in tests were increased. In this research, conditions included the difference of type of test, group of sample size, levels of test length, and and rate of mix of some items lacking  local independence. The research findings were (1) The results of the analysis of the index change to detect local independence of items, it was found that goodness of fit index consist of CMIN/DF, RMR,  GFI, AGFI, IFI and RMSEA yield similar goodness of fit index that all of 20 tests were mixed testlet were unidimensionality, In addition, when number of item interaction in tests were increased, goodness of fit index decresed.

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จงกล บัวแก้ว, ไพรัตน์ วงษ์นาม และ สมพงษ์ ปั้นหุ่น. (2561). การประมาณค่าพารามิเตอร์ของแบบสอบเทสต์เลทตามโมเดลทฤษฎีการตอบสนองข้อสอบและโมเดลทฤษฎีการตอบสนองเทสต์เลท. วารสารราชภัฏสุราษฎร์ธานี, 5(1), 139-155.
วรนุช แหยมแสง. (2537). การพัฒนากระบวนการตรวจสอบความเป็นเอกมิติของแบบสอบ. วิทยานิพนธ์ปริญญาดุษฎีบัณฑิต ภาควิชาวิจัยการศึกษา จุฬาลงกรณ์มหาวิทยาลัย.
Allen, M. J., & Yen, W. M. (1979). Introduction to measurement theory. Monterey, Calif.: Brooks/Cole Pub. Co.
Baghaei, P. & Ravand, H. (2016). Modeling local item dependence in cloze and reading comprehension test items using testlet response theory. Psicológica, 37, 85-104.
Brandt, S. (2012). Robustness of multidimensional analyses against local item dependence. Psychological Test and Assessment Modeling, 54(1), 36-53.
Cao, Y., Lu, R., & Tao, W. (2014). Effect of item response theory (irt) model selection on testlet-based test equating. ETS Research Report Series, 2014(2), 1-13. doi.org/10.1002/ets2.12017
Eckes, T. & Baghaeib, P. (2015). Using testlet response theory to examine local dependence in c-tests. Applied Measurement in Education, 28, 85–98. DOI: 10.1080/08957347.2014.1002919
Edwards, M. C. & Cai, Li. (2011). A new procedure for detecting departures from local independence in item response models. CA: Department of Psychology, The Ohio State University.
Hambleton, R. K. & Swaminathan, H. (1985). Item response theory: Principles and application. Boston: Kluwer-Nyjhoff.
Hambleton, R. K., & Traub, R. E. (1974). The effects of item order on test performance and stress. Journal of Experimental Education, 43(1), 40–46. https://doi.org/10.1080/ 00220973.1974.10806302
Jiao, H., Wang, S., & He, W. (2013). Estimation methods for one-parameter testlet models. Journal of Educational Measurement, 50, 186–203. DOI: 10.1111/jedm.12010
Li, F. (2017). An information-correction method for testlet-based test analysis: From the perspectives of item response theory and generalizability theory. ETS Research Report Series, 2017, 1-25. doi.org/10.1002/ets2.12151
Liu, Y. & Maydeu-Olivares, A. (2012). Local dependence diagnostics in irt modeling of binary data. Educational and Psychological Measurement, 73(2), 254–274. DOI: 10.1177/0013164412453841
Lord, F. M. (1980). Application of item response theory to practical testing problems. Hillsdak NJ: Erlbaum.
McDonald, R. P. (1983). Exploratory and confirmatory nonlinear confirmatory nonlinear common factor analysis. In H. Wainer and S. Messick (Eds), Principals of modern psychological measurement: A Festschrift for Frederic M.Lord. Hillsdale NJ: Erlbaum. (p.197-213).
Nandakumar, R. & Stout, W. (1993) Refinements of stout's procedure for assessing latent trait unidimensionalit. Journal of Educational Statistics, 18, 41-68.
Rajlic, G. (2019). Violations of unidimensionality and local independence in measures intended as unidimensional: assessing levels of violations and the accuracy in unidimensional irt model estimates (Doctoral dissertation). the University of British Columbia, Vancouver, Canada. DOI: 10.14288/1.0380235
Ravand, H. (2015). Assessing testlet effect, impact, differential testlet, and item functioning using cross-classified multilevel measurement modeling. SAGE Open, (April-June 2015), 1–9. DOI: 10.1177/2158244015585607
Roznowski, M., Tucker, L. R., & Humphreys, L. G. (1991). Three approaches to determining the dimensioinality of binary items. Applied Psychological Measurement, 15, 109-127.
Rubright, J. D. (2018). Impact of both local item dependencies and cut-point locations on examinee classifications. Educational Measurement: Issues and Practice, 37(3), 40-45. DOI: 10.1111/emip.12183
Setiawati, F. A., Izzaty, R. E., & Hidayat, V. (2018). Items parameters of the space-relations subtest using item response theory. Data in Brief, 19(2018), 1785–1793. doi.org/10.1016/j.dib. 2018.06.061
Sireci, S. G., Thissen, D., & Wainer, H. (1991). On the reliability of testlet-based tests. Journal of Educational Measurement, 28(3), 237-247. https://www.jstor.org/stable/1434845
Tao, W. & Cao, Y. (2016). An extension of IRT-based equating to the dichotomous testlet response theory model. Applied Measurement in Education, 29(2), 108–121.
Van den Wollenberg, A. L. (1982). Two new test statistics for the Rasch model. Psychometrika, 47(2), 123–140. https://doi.org/10.1007/BF02296270
Wainer, H., Bradlow, E. T., &Wang, X. (2007). Testlet response theory and its applications. New York, NY: Cambridge University Press. doi.org/10.1017/ CBO9780511618765
Warm, T. A. (1978). A primer of item response theory. Oklahoma: Coast Guard Institute.
Yen, W. M. (1984). Effect of local item dependence on the fit and equating performance of the three-parameter logistic model. Applied Psychological Measurement, 8, 125-145.
Zhan, P., Liao, M., & Bian, Y. (2018). Joint testlet cognitive diagnosis modeling for paired local item dependence in response times and response accuracy. the Journal Frontiers in Psychology, 9(April 2018), 1-14. DOI: 10.3389/fpsyg. 2018.00607