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stat.ME2023
Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment
Siyu Heng, Jiawei Zhang, Yang Feng
Design-based causal inference, also known as randomization-based or finite-population causal inference, is one of the most widely used causal inference frameworks, largely due to t…
stat.ME2023★ 3 cited
-penalized Multinomial Regression: Estimation, inference, and prediction, with an application to risk factor identification for different dementia subtypes
Ye Tian, Henry Rusinek, Arjun V. Masurkar +1
High-dimensional multinomial regression models are very useful in practice but have received less research attention than logistic regression models, especially from the perspectiv…