| Data-driven learning of Q-matrix J Liu, G Xu, Z Ying Applied psychological measurement 36 (7), 548-564, 2012 | 224 | 2012 |
| Statistical analysis of Q-matrix based diagnostic classification models Y Chen, J Liu, G Xu, Z Ying Journal of the American Statistical Association 110 (510), 850-866, 2015 | 202 | 2015 |
| A mixture hierarchical model for response times and response accuracy C Wang, G Xu British Journal of Mathematical and Statistical Psychology 68 (3), 456-477, 2015 | 190 | 2015 |
| Identifiability of diagnostic classification models G Xu, S Zhang Psychometrika 81, 625-649, 2016 | 134 | 2016 |
| Identifiability of restricted latent class models with binary responses G Xu The Annals of Statistics 45 (2), 675-707, 2017 | 130 | 2017 |
| Identifying latent structures in restricted latent class models G Xu, Z Shang Journal of the American Statistical Association 113 (523), 1284-1295, 2018 | 125 | 2018 |
| Theory of the self-learning Q-matrix J Liu, G Xu, Z Ying Bernoulli: official journal of the Bernoulli Society for Mathematical …, 2013 | 105 | 2013 |
| An adaptive two-sample test for high-dimensional means G Xu, L Lin, P Wei, W Pan Biometrika 103 (3), 609-624, 2016 | 98 | 2016 |
| The sufficient and necessary condition for the identifiability and estimability of the DINA model Y Gu, G Xu Psychometrika 84, 468-483, 2019 | 81 | 2019 |
| A two-stage approach to differentiating normal and aberrant behavior in computer based testing C Wang, G Xu, Z Shang Psychometrika 83, 223-254, 2018 | 75 | 2018 |
| Partial identifiability of restricted latent class models Y Gu, G Xu Annals of Statistics 48 (4), 2082-2107, 2020 | 69 | 2020 |
| Red cell distribution width is associated with presence, stage, and grade in patients with renal cell carcinoma FM Wang, G Xu, Y Zhang, LL Ma Disease markers 2014 (1), 860419, 2014 | 64 | 2014 |
| Detecting aberrant behavior and item preknowledge: A comparison of mixture modeling method and residual method C Wang, G Xu, Z Shang, N Kuncel Journal of Educational and Behavioral Statistics 43 (4), 469-501, 2018 | 62 | 2018 |
| Asymptotically independent U-statistics in high-dimensional testing Y He, G Xu, C Wu, W Pan Annals of Statistics 49 (1), 154-181, 2021 | 53 | 2021 |
| Sufficient and Necessary Conditions for the Identifiability of the -matrix Y Gu, G Xu Statistica Sinica 31, 449-472, 2021 | 52 | 2021 |
| Observation of the polaronic character of excitons in a two-dimensional semiconducting magnet CrI3 W Jin, HH Kim, Z Ye, G Ye, L Rojas, X Luo, B Yang, F Yin, JSA Horng, ... Nature communications 11 (1), 4780, 2020 | 45 | 2020 |
| On initial item selection in cognitive diagnostic computerized adaptive testing G Xu, C Wang, Z Shang British Journal of Mathematical and Statistical Psychology 69 (3), 291-315, 2016 | 38 | 2016 |
| Model based bootstrap methods for interval censored data B Sen, G Xu Computational Statistics & Data Analysis 81, 121-129, 2015 | 35 | 2015 |
| Learning attribute patterns in high-dimensional structured latent attribute models Y Gu, G Xu Journal of Machine Learning Research 20 (115), 1-58, 2019 | 34 | 2019 |
| Debiased inference on treatment effect in a high-dimensional model J Wang, X He, G Xu Journal of the American Statistical Association, 2019 | 30 | 2019 |
