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High-dimensional Exploratory Item Factor Analysis by A Metropolis–Hastings Robbins–Monro Algorithm

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Cited by:

  1. Justin L. Kern, 2024. "Extending an Identified Four-Parameter IRT Model: The Confirmatory Set-4PNO Model," Journal of Educational and Behavioral Statistics, , vol. 49(3), pages 368-402, June.
  2. Siliang Zhang & Yunxiao Chen, 2022. "Computation for Latent Variable Model Estimation: A Unified Stochastic Proximal Framework," Psychometrika, Springer;The Psychometric Society, vol. 87(4), pages 1473-1502, December.
  3. Nuo Xi & Michael W. Browne, 2014. "Contributions to the Underlying Bivariate Normal Method for Factor Analyzing Ordinal Data," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 583-611, December.
  4. Yang Liu & Jan Hannig, 2017. "Generalized Fiducial Inference for Logistic Graded Response Models," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1097-1125, December.
  5. Chun Wang, 2015. "On Latent Trait Estimation in Multidimensional Compensatory Item Response Models," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 428-449, June.
  6. Yunxiao Chen, 2020. "A Continuous-Time Dynamic Choice Measurement Model for Problem-Solving Process Data," Psychometrika, Springer;The Psychometric Society, vol. 85(4), pages 1052-1075, December.
  7. Björn Andersson & Tao Xin, 2021. "Estimation of Latent Regression Item Response Theory Models Using a Second-Order Laplace Approximation," Journal of Educational and Behavioral Statistics, , vol. 46(2), pages 244-265, April.
  8. Merkle, Edgar C. & Steyvers, Mark & Mellers, Barbara & Tetlock, Philip E., 2017. "A neglected dimension of good forecasting judgment: The questions we choose also matter," International Journal of Forecasting, Elsevier, vol. 33(4), pages 817-832.
  9. Jianan Sun & Yunxiao Chen & Jingchen Liu & Zhiliang Ying & Tao Xin, 2016. "Latent Variable Selection for Multidimensional Item Response Theory Models via $$L_{1}$$ L 1 Regularization," Psychometrika, Springer;The Psychometric Society, vol. 81(4), pages 921-939, December.
  10. Sijia Huang & Li Cai, 2021. "Lord–Wingersky Algorithm Version 2.5 with Applications," Psychometrika, Springer;The Psychometric Society, vol. 86(4), pages 973-993, December.
  11. Harald Hruschka, 2021. "Comparing unsupervised probabilistic machine learning methods for market basket analysis," Review of Managerial Science, Springer, vol. 15(2), pages 497-527, February.
  12. Seungwon Chung & Li Cai, 2021. "Cross-Classified Random Effects Modeling for Moderated Item Calibration," Journal of Educational and Behavioral Statistics, , vol. 46(6), pages 651-681, December.
  13. Haoran Zhang & Yunxiao Chen & Xiaoou Li, 2020. "A Note on Exploratory Item Factor Analysis by Singular Value Decomposition," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 358-372, June.
  14. Motonori Oka & Kensuke Okada, 2023. "Scalable Bayesian Approach for the Dina Q-Matrix Estimation Combining Stochastic Optimization and Variational Inference," Psychometrika, Springer;The Psychometric Society, vol. 88(1), pages 302-331, March.
  15. Li Cai, 2015. "Lord–Wingersky Algorithm Version 2.0 for Hierarchical Item Factor Models with Applications in Test Scoring, Scale Alignment, and Model Fit Testing," Psychometrika, Springer;The Psychometric Society, vol. 80(2), pages 535-559, June.
  16. Li Cai & Carrie R. Houts, 2021. "Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 86(3), pages 754-777, September.
  17. Ting Wang & Benjamin Graves & Yves Rosseel & Edgar C. Merkle, 2022. "Computation and application of generalized linear mixed model derivatives using lme4," Psychometrika, Springer;The Psychometric Society, vol. 87(3), pages 1173-1193, September.
  18. Li Cai, 2010. "Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis," Journal of Educational and Behavioral Statistics, , vol. 35(3), pages 307-335, June.
  19. Gregory Camilli & Jean-Paul Fox, 2015. "An Aggregate IRT Procedure for Exploratory Factor Analysis," Journal of Educational and Behavioral Statistics, , vol. 40(4), pages 377-401, August.
  20. Zhehan Jiang & Jonathan Templin, 2019. "Gibbs Samplers for Logistic Item Response Models via the Pólya–Gamma Distribution: A Computationally Efficient Data-Augmentation Strategy," Psychometrika, Springer;The Psychometric Society, vol. 84(2), pages 358-374, June.
  21. Yunxiao Chen & Xiaoou Li & Siliang Zhang, 2019. "Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 124-146, March.
  22. Andrej Srakar & Vesna Čopič & Miroslav Verbič, 2018. "European cultural statistics in a comparative perspective: index of economic and social condition of culture for the EU countries," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 42(2), pages 163-199, May.
  23. Matthias Davier & Xueli Xu & Claus Carstensen, 2011. "Measuring Growth in a Longitudinal Large-Scale Assessment with a General Latent Variable Model," Psychometrika, Springer;The Psychometric Society, vol. 76(2), pages 318-336, April.
  24. Ji Seung Yang & Li Cai, 2014. "Estimation of Contextual Effects Through Nonlinear Multilevel Latent Variable Modeling With a Metropolis–Hastings Robbins–Monro Algorithm," Journal of Educational and Behavioral Statistics, , vol. 39(6), pages 550-582, December.
  25. Nicholas J. Rockwood, 2021. "Efficient Likelihood Estimation of Generalized Structural Equation Models with a Mix of Normal and Nonnormal Responses," Psychometrika, Springer;The Psychometric Society, vol. 86(2), pages 642-667, June.
  26. April E. Cho & Jiaying Xiao & Chun Wang & Gongjun Xu, 2024. "Regularized Variational Estimation for Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 89(1), pages 347-375, March.
  27. Christopher J. Urban & Daniel J. Bauer, 2021. "A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 86(1), pages 1-29, March.
  28. Heon-Jae Jeong & Hsun-Hsiang Liao & Su Ha Han & Wui-Chiang Lee, 2020. "An Application of Item Response Theory to Scoring Patient Safety Culture Survey Data," IJERPH, MDPI, vol. 17(3), pages 1-10, January.
  29. Chen-Wei Liu & Björn Andersson & Anders Skrondal, 2020. "A Constrained Metropolis–Hastings Robbins–Monro Algorithm for Q Matrix Estimation in DINA Models," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 322-357, June.
  30. Scott Monroe, 2019. "Estimation of Expected Fisher Information for IRT Models," Journal of Educational and Behavioral Statistics, , vol. 44(4), pages 431-447, August.
  31. Zhang, Siliang & Chen, Yunxiao, 2022. "Computation for latent variable model estimation: a unified stochastic proximal framework," LSE Research Online Documents on Economics 114489, London School of Economics and Political Science, LSE Library.
  32. Yang Liu & Jan Hannig, 2016. "Generalized Fiducial Inference for Binary Logistic Item Response Models," Psychometrika, Springer;The Psychometric Society, vol. 81(2), pages 290-324, June.
  33. Yoav Bergner & Peter Halpin & Jill-Jênn Vie, 2022. "Multidimensional Item Response Theory in the Style of Collaborative Filtering," Psychometrika, Springer;The Psychometric Society, vol. 87(1), pages 266-288, March.
  34. Yang Liu & Weimeng Wang, 2024. "What Can We Learn from a Semiparametric Factor Analysis of Item Responses and Response Time? An Illustration with the PISA 2015 Data," Psychometrika, Springer;The Psychometric Society, vol. 89(2), pages 386-410, June.
  35. Cardenas Hurtado, Camilo & Moustaki, Irini & Chen, Yunxiao & Marra, Giampiero, 2025. "Generalized latent variable models for location, scale, and shape parameters," LSE Research Online Documents on Economics 127387, London School of Economics and Political Science, LSE Library.
  36. Yang Liu, 2020. "A Riemannian Optimization Algorithm for Joint Maximum Likelihood Estimation of High-Dimensional Exploratory Item Factor Analysis," Psychometrika, Springer;The Psychometric Society, vol. 85(2), pages 439-468, June.
  37. Battauz, Michela & Vidoni, Paolo, 2022. "A likelihood-based boosting algorithm for factor analysis models with binary data," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  38. Chenchen Ma & Jing Ouyang & Chun Wang & Gongjun Xu, 2024. "A Note on Improving Variational Estimation for Multidimensional Item Response Theory," Psychometrika, Springer;The Psychometric Society, vol. 89(1), pages 172-204, March.
  39. Yang Liu & Weimeng Wang, 2022. "Semiparametric Factor Analysis for Item-Level Response Time Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 666-692, June.
  40. Li Cai, 2010. "A Two-Tier Full-Information Item Factor Analysis Model with Applications," Psychometrika, Springer;The Psychometric Society, vol. 75(4), pages 581-612, December.
  41. Peida Zhan & Hong Jiao & Dandan Liao & Feiming Li, 2019. "A Longitudinal Higher-Order Diagnostic Classification Model," Journal of Educational and Behavioral Statistics, , vol. 44(3), pages 251-281, June.
  42. Sijia Huang & Li Cai, 2024. "Cross-Classified Item Response Theory Modeling With an Application to Student Evaluation of Teaching," Journal of Educational and Behavioral Statistics, , vol. 49(3), pages 311-341, June.
  43. Zhang, Haoran & Chen, Yunxiao & Li, Xiaoou, 2020. "A note on exploratory item factor analysis by singular value decomposition," LSE Research Online Documents on Economics 104166, London School of Economics and Political Science, LSE Library.
  44. Chengyu Cui & Chun Wang & Gongjun Xu, 2024. "Variational Estimation for Multidimensional Generalized Partial Credit Model," Psychometrika, Springer;The Psychometric Society, vol. 89(3), pages 929-957, September.
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