Evaluating model estimation processes for diagnostic classification models
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[1] Andrew Izsák,et al. Diagnosing Teachers’ Understandings of Rational Numbers: Building a Multidimensional Test Within the Diagnostic Classification Framework , 2014 .
[2] Jonathan Templin,et al. Extending Cognitive Diagnosis Models to Evaluate the Validity of DSM Criteria for the Diagnosis of Pathological Gambling , 2007 .
[3] De Ayala,et al. The Theory and Practice of Item Response Theory , 2008 .
[4] M. Reckase. Multidimensional Item Response Theory , 2009 .
[5] Richard A. Feinberg,et al. Conducting Simulation Studies in Psychometrics , 2016 .
[6] Yihui Xie,et al. A General-Purpose Package for Dynamic Report Generation in R , 2016 .
[7] R. Devellis. Classical Test Theory , 2006, Medical care.
[8] Geraldine Lear,et al. Standard setting. , 2003, Nursing standard (Royal College of Nursing (Great Britain) : 1987).
[9] Jeffrey A Douglas,et al. Higher-order latent trait models for cognitive diagnosis , 2004 .
[10] Laine Bradshaw,et al. An Illustration of Diagnostic Classification Modeling in Student Learning Outcomes Assessment , 2014 .
[11] D. Vats. Simulation and the Monte Carlo Method, 3rd ed. , 2019, Journal of the American Statistical Association.
[12] Jimmy de la Torre,et al. Analysis of Clinical Data From Cognitive Diagnosis Modeling Framework , 2015 .
[13] Jeffrey A Douglas,et al. Test Construction for Cognitive Diagnosis , 2005 .
[14] Howard Wainer,et al. When Can We Improve Subscores by Making Them Shorter?: The Case Against Subscores with Overlapping Items , 2014 .
[15] Tapabrata Maiti,et al. Principles and Practice of Structural Equation Modeling (2nd ed.) , 2006 .
[16] N. Lazar,et al. The ASA Statement on p-Values: Context, Process, and Purpose , 2016 .
[17] L. T. DeCarlo. On the Analysis of Fraction Subtraction Data: The DINA Model, Classification, Latent Class Sizes, and the Q-Matrix , 2011 .
[18] Jacob Cohen,et al. Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. , 1968 .
[19] Phil Wood. Confirmatory Factor Analysis for Applied Research , 2008 .
[20] Neal M. Kingston,et al. Assessing the Structure of the GRE General Test Using Confirmatory Multidimensional Item Response Theory. , 1988 .
[21] W. Stroup. Generalized Linear Mixed Models: Modern Concepts, Methods and Applications , 2012 .
[22] Hadley Wickham,et al. Make Dealing with Dates a Little Easier , 2015 .
[23] Matthias von Davier,et al. FITTING THE STRUCTURED GENERAL DIAGNOSTIC MODEL TO NAEP DATA , 2008 .
[24] Shelby J. Haberman,et al. Do Adjusted Subscores Lack Validity? Don’t Blame the Messenger , 2011 .
[25] Andrew Gelman,et al. Data Analysis Using Regression and Multilevel/Hierarchical Models , 2006 .
[26] Lisa L. Harlow,et al. An Illustration of a Longitudinal Cross-Lagged Design for Larger Structural Equation Models , 2003 .
[27] Russell G. Almond,et al. Bayesian Networks in Educational Assessment , 2015 .
[28] G. Schwarz. Estimating the Dimension of a Model , 1978 .
[29] L. Corrado. Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models , 2005 .
[30] H. Akaike. A new look at the statistical model identification , 1974 .
[31] Wenchao Ma. Diagnostic Measurement: Theory, Methods, and Applications , 2018 .
[32] David Thissen,et al. A taxonomy of item response models , 1986 .
[33] J. Templin,et al. Measurement of psychological disorders using cognitive diagnosis models. , 2006, Psychological methods.
[34] Joshua F. Wiley,et al. MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus , 2018, Structural equation modeling : a multidisciplinary journal.
[35] André A. Rupp,et al. The Impact of Model Misspecification on Parameter Estimation and Item‐Fit Assessment in Log‐Linear Diagnostic Classification Models , 2012 .
[36] K. Tatsuoka. RULE SPACE: AN APPROACH FOR DEALING WITH MISCONCEPTIONS BASED ON ITEM RESPONSE THEORY , 1983 .
[37] Edward H. Haertel. Using restricted latent class models to map the skill structure of achievement items , 1989 .
[38] J. Templin,et al. Unique Characteristics of Diagnostic Classification Models: A Comprehensive Review of the Current State-of-the-Art , 2008 .
[39] B. Junker,et al. Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric Item Response Theory , 2001 .
[40] M. Reckase. The Past and Future of Multidimensional Item Response Theory , 1997 .
[41] Alan Agresti,et al. Categorical Data Analysis, 3rd Edition Extra Exercises , 2012 .
[42] Sandip Sinharay,et al. When Can Subscores Be Expected to Have Added Value? Results from Operational and Simulated Data. Research Report. ETS RR-10-16. , 2010 .
[43] S. Chinn. A simple method for converting an odds ratio to effect size for use in meta-analysis. , 2000, Statistics in medicine.
[44] Laine Bradshaw,et al. Hierarchical Diagnostic Classification Models: A Family of Models for Estimating and Testing Attribute Hierarchies , 2014, Psychometrika.
[45] Michael R. Harwell,et al. Monte Carlo Studies in Item Response Theory , 1996 .
[46] Laine Bradshaw. Diagnostic Classification Models , 2016 .
[47] Jacob Cohen. A Coefficient of Agreement for Nominal Scales , 1960 .
[48] Z. Ying,et al. Statistical Analysis of Q-Matrix Based Diagnostic Classification Models , 2015, Journal of the American Statistical Association.
[49] John T. Willse,et al. Defining a Family of Cognitive Diagnosis Models Using Log-Linear Models with Latent Variables , 2009 .
[50] G. Cizek,et al. Setting performance standards : foundations, methods, and innovations , 2012 .
[51] Sarah M. Hartz,et al. A Bayesian framework for the unified model for assessing cognitive abilities: Blending theory with practicality. , 2002 .
[52] Laine Bradshaw,et al. Combining Item Response Theory and Diagnostic Classification Models: A Psychometric Model for Scaling Ability and Diagnosing Misconceptions , 2014, Psychometrika.
[53] Matthew Rockloff,et al. An SEM Algorithm for Scale Reduction Incorporating Evaluation of Multiple Psychometric Criteria , 2018 .
[54] Yihui Xie,et al. bookdown: Authoring Books and Technical Documents with R Markdown , 2016 .
[55] S. Sclove. Application of model-selection criteria to some problems in multivariate analysis , 1987 .
[56] Jan-Willem Romeijn,et al. ‘All models are wrong...’: an introduction to model uncertainty , 2012 .
[57] Pascal Bouvry,et al. Amazon Elastic Compute Cloud (EC2) vs. In-House HPC Platform: A Cost Analysis , 2016, 2016 IEEE 9th International Conference on Cloud Computing (CLOUD).
[58] Akihito Kamata,et al. A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items , 2011 .
[59] K. Tatsuoka. Toward an Integration of Item-Response Theory and Cognitive Error Diagnosis. , 1987 .
[60] R Core Team,et al. R: A language and environment for statistical computing. , 2014 .
[61] Jimmy de la Torre,et al. An Empirically Based Method of Q‐Matrix Validation for the DINA Model: Development and Applications , 2008 .
[62] P. Hewson. Bayesian Data Analysis 3rd edn A. Gelman, J. B. Carlin, H. S. Stern, D. B. Dunson, A. Vehtari and D. B. Rubin, 2013 Boca Raton, Chapman and Hall–CRC 676 pp., £44.99 ISBN 1‐439‐84095‐4 , 2015 .
[63] Jj Allaire,et al. Dynamic Documents for R , 2016 .
[64] J. Templin,et al. The Effects of Q-Matrix Misspecification on Parameter Estimates and Classification Accuracy in the DINA Model , 2008 .
[65] John L. Perry,et al. Assessing Model Fit: Caveats and Recommendations for Confirmatory Factor Analysis and Exploratory Structural Equation Modeling , 2015 .