Scholarly and Creative Works
2025
- Liu, D., Lin, Z., & Zhang, H. (2025). A unified framework for residual diagnostics in generalized linear models and beyond. The Journal of the American Statistical Association. https://doi.org/https://doi.org/10.1080/01621459.2025.2504037
2024
- Zhu, X., Lin, Z., Liu, D., & Greenwell, B. (2024). SurrogateRsq: An R Package for Categorical Data Goodness-of-Fit Analysis Using the Surrogate R2. The New England Journal of Statistics in Data Science, 1–12. Retrieved from https://nejsds.nestat.org/journal/NEJSDS/article/77/text
2022
- Liu, D., Zhu, X., Greenwell, B., & Lin, Z. (2022). A new goodness-of-fit measure for probit models: Surrogate R2. British Journal of Mathematical and Statistical Psychology, 76(1), 192–210. Retrieved from https://bpspsychub.onlinelibrary.wiley.com/doi/full/10.1111/bmsp.12289