Author:
He Siqi,Culpepper Steven Andrew,Douglas Jeff
Publisher
Springer International Publishing
Reference41 articles.
1. Allman, E. S., Matias, C., Rhodes, J. A., et al. (2009). Identifiability of parameters in latent structure models with many observed variables. The Annals of Statistics, 37(6), 3099–3132. https://doi.org/10.1214/09-AOS689
2. Bolt, D. M., & Kim, J.-S. (2018). Parameter invariance and skill attribute continuity in the DINA model. Journal of Educational Measurement, 55(2), 264–280. https://doi.org/10.1111/jedm.12175
3. Chen, Y., Culpepper, S., & Liang, F. (2020). A sparse latent class model for cognitive diagnosis. Psychometrika, 85(1), 121–153. https://doi.org/10.1007/s11336-019-09693-2
4. Chen, Y., & Culpepper, S. A. (2020). A multivariate probit model for learning trajectories: A fine-grained evaluation of an educational intervention. Applied Psychological Measurement, 44(7–8), 515–530. https://doi.org/10.1177/0146621620920928
5. Chen, Y., Liu, Y., Culpepper, S. A., & Chen, Y. (2021). Inferring the number of attributes for the exploratory DINA model. Psychometrika, 86(1), 30–64. https://doi.org/10.1007/s11336-021-09750-9