Abstract
Because the validity of diagnostic information generated by cognitive diagnosis models (CDMs) depends on the appropriateness of the estimated attribute profiles, it is imperative to ensure the accurate measurement of students’ test performance by conducting person fit (PF) evaluation to avoid flawed remediation measures. The standardized log-likelihood statistic lZ has been extended to the CDM framework. However, its null distribution is found to be negatively skewed. To address this issue, this study applies different methods of adjusting the skewness of lZ that have been proposed in the item response theory context, namely, χ2-approximation, Cornish-Fisher expansion, and Edgeworth expansion to bring its null distribution closer to the standard normal distribution. The skewness-corrected PF statistics are investigated by calculating their type I error and detection rates using a simulation study. Fraction-subtraction data are also used to illustrate the application of these PF statistics.
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References
Bedrick, E. J. (1997). Approximating the conditional distribution of person fit indexes for checking the Rasch model. Psychometrika, 62, 191–199.
Conjin, J. M. (2013). Detecting and explaining person misfit in non-cognitive measurement. Ridderkerk: Ridderprint.
Cui, Y., & Leighton, J. O. (2009). The hierarchy consistency index: evaluating person fit for cognitive diagnostic assessment. Journal of Educational Measurement, 46, 429–449.
Cui, Y., & Li, J. (2015). Evaluating person fit for cognitive diagnostic assessment. Applied Psychological Measurement, 39, 223–238.
Cui, Y., & Roberts, M. R. (2013). Validating student score inferences with person-fit statistic and verbal reports: a person-fit study for cognitive diagnostic assessment. Educational Measurement: Issues and Practice, 32, 34–42.
Cui, Y., Gierl, M. J., & Chang, H. H. (2012). Estimating classification consistency and accuracy for cognitive diagnostic assessment. Journal of Educational Measurement, 49, 19–38.
de la Torre, J. (2009). DINA model and parameter estimation: a didactic. Journal of Educational and Behavioral Statistics, 34, 115–130.
de la Torre, J. (2011). The generalized DINA model framework. Psychometrika, 76, 179–199.
de la Torre, J., & Deng, W. (2008). Improving person fit assessment by correcting the ability estimate and its reference distribution. Journal of Educational Measurement, 45, 159–177.
de la Torre, J., & Minchen, N. (2014). Cognitively diagnostic assessments and the cognitive diagnosis model framework. Psicologa Educativa, 20, 89–97.
Drasgow, F., Levine, M. V., & Williams, E. A. (1985). Appropriateness measurement with polychotomous item response models and standardized indices. British Journal of Mathematical and Statistical Psychology, 38, 67–86.
Glas, C. A. W., & Dagohoy, A. V. T. (2007). A person fit test for IRT models for polytomous items. Psychometrika, 72, 159–180.
Haertel, E. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26, 301–321.
Hartz, S. M. (2002). A Bayesian framework for the unified model for assessing cognitive abilities: blending theory with practicality, unpublished doctoral dissertation, University of Illinois at Urbana–Champaign, Urbana–Champaign, IL.
Henson, R. A., Templin, J. L., & Willse, J. T. (2009). Defining a family of cognitive diagnosis models using log-linear models with latent variables. Psychometrika, 74, 191–210.
Hulin, C. L., Drasgow, F., & Parsons, C. K. (1983). Item response theory: application to psychological measurement. Homewood: Dow Jones-Irwin.
Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258–272.
Levine, M. V., & Drasgow, F. (1983). Appropriateness measurement: validating studies and variable ability models. In D. J. Weiss (Ed.), New horizons in testing: latent trait test theory and computerized adaptive testing (pp. 109–131). New York: Academic Press.
Levine, M. V., & Rubin, D. B. (1979). Measuring the appropriateness of multiple choice test scores. Journal of Educational Statistics, 4, 269–290.
Liu, Y., Douglas, J., & Henson, R. (2009). Testing person fit in cognitive diagnosis. Applied Psychological Measurement, 33, 579–598.
Ma, W., & de la Torre, J (2017). GDINA: the generalized DINA model framework. R package version 1.4.2, Available at https://CRAN.R-project.org/package=GDINA.
Ma, W., Iaconangelo, C., & de la Torre, J. (2016). Model similarity, model selection, and attribute classification. Applied Psychological Measurement, 40, 200–217.
Mccullagh, E. (1986). The conditional distribution of goodness-of-fit statistics for discrete data. Journal of the American Statistical Association, 81, 104–107.
Meijer, R., & Nering, M. L. (1997). Trait level estimation for nonfitting response vectors. Applied Psychological Measurement, 21, 321–336.
Molenaar, I. W., & Hoijtink, H. (1990). The many null distributions of person fit indices. Psychometrika, 55, 75–106.
Nering, M. L. (1995). The distribution of person fit using true and estimated person parameters. Applied Psychological Measurement, 19, 121–129.
Nering, M. L. (1997). The distribution of indexes of person-fit within the computerized adaptive testing environment. Applied Psychological Measurement, 21, 115–127.
Reise, S. P. (1995). Scoring method and the detection of person misfit in a personality assessment context. Applied Psychological Measurement, 19, 213–229.
Rupp, A. A., & Templin, J. (2008). Unique characteristics of diagnostic classification models: a comprehensive review of the current state-of-the-art. Measurement: Interdisciplinary Research and Perspectives, 6, 219–262.
Sinharay, S. (2015). Assessing person fit using lZ* and the posterior predictive model checking method for dichotomous item response theory models. International Journal of Quantitative Research in Education, 2, 265–284.
Sinharay, S. (2016). Assessment of person fit using resampling-based approaches. Journal of Educational Measurement, 53, 63–85.
Snijders, T. (2001). Asymptotic distribution of person-fit statistics with estimated person parameter. Psychometrika, 66, 331–342.
Tatsuoka, K. K. (1983). Rule space: an approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement, 20, 345–354.
Tatsuoka, K. K. (1984). Caution indices based on item response theory. Psychometrika, 49, 95–110.
Tatsuoka, K. K. (1990). Toward an integration of item-response theory and cognitive error diagnosis. In N. Frederiksen, R. Glaser, A. Lesgold, & M. Safto (Eds.), Monitoring skills and knowledge acquisition (pp. 453–488). Hillsdale: Erlbaum.
Templin, J. L., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11, 287–305.
Von Davier, M. (2008). A general diagnostic model applied to language testing data. British Journal of Mathematical and Statistical Psychology, 61, 287–307.
Von Davier, M., & Molenaar, I. (2003). A person-fit index for polytomous rasch models, latent class models, and their mixture generalizations. Psychometrika, 68, 213–228.
Wright, B. D. (1977). Solving measurement problems with the Rasch model. Journal of Educational Measurement, 14, 97–115.
Funding
This research was funded by the Philippine Commission on Higher Education, Philippine Social Science Council, and University of the Philippines-Diliman. Moreover, this research was carried out in part using the CoARE Facility of the DOST-Advance Science and Technology Institute and the Computing and Archiving Research Environment (CoARE) Project.
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Santos, K.C.P., de la Torre, J. & von Davier, M. Adjusting Person Fit Index for Skewness in Cognitive Diagnosis Modeling. J Classif 37, 399–420 (2020). https://doi.org/10.1007/s00357-019-09325-5
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DOI: https://doi.org/10.1007/s00357-019-09325-5