| Predictive feature generation and selection using process data from PISA interactive problem-solving items: An application of random forests Z Han, Q He, M von Davier Frontiers in psychology 10, 2461, 2019 | 43 | 2019 |
| Global-and item-level model fit indices Z Han, MS Johnson Handbook of Diagnostic Classification Models: Models and Model Extensions …, 2019 | 9 | 2019 |
| Exploring process data in problem-solving items in computer-based large-scale assessments Q He, M von Davier, Z Han Data analytics and psychometrics: Informing assessment practices, 53-76, 2018 | 7 | 2018 |
| Exploring process data in computer-based international large-scale assessments Q He, M von Davier, Z Han Data analytics and psychometrics: Informing assessment practices, 53-76, 2018 | 5 | 2018 |
| Predictive feature generation and selection using process data from PISA simulation-based environment: An application of tree-based ensemble methods Z Han, Q He, M von Davier Frontiers in Psychology 10, 1421, 2019 | 4 | 2019 |
| The UMP exact test and the confidence interval for person parameters in IRT models X Liu, Z Han, MS Johnson psychometrika 83, 182-202, 2018 | 4 | 2018 |
| The Standardized S-X2 Statistic for Assessing Item Fit Z Han, S Sinharay, MS Johnson, X Liu Applied Psychological Measurement 47 (1), 3-18, 2023 | 1 | 2023 |
| Exploring process data in problem-solving items in computer-based large-scale assessments: Case studies in PISA and PIAAC. Q He, M von Davier, Z Han Information Age Publishing, Inc., 2019 | 1 | 2019 |
| Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement Z Han Columbia University, 2019 | | 2019 |
