6 papers
Bregman projection for calibration estimation in Survey Sampling
Jae Kwang Kim, Yonghyun Kwon, Yumou Qiu
Calibration weighting is a fundamental tool in survey sampling for incorporating auxiliary population information into design-based estimators. Classical formulations measure dista…
MEC-Cox: Machine-Learning-Assisted Generalized Entropy Calibration for ATT Marginal Hazard-Ratio Estimation
Se Yoon Lee, Yonghyun Kwon, Jae Kwang Kim
Externally controlled survival trials are increasingly used when concurrent randomized controls are infeasible, particularly in oncology and rare-disease settings with time-to-even…
Sample-split REGression SREG: A robust estimator for high-dimensional survey data
Yonghyun Kwon, Shu Yang, Jae Kwang Kim
Model-assisted regression estimation is fundamental in survey sampling for incorporating auxiliary information. However, when the auxiliary dimension grows with the sample size, th…
A General Approach for Calibration Weighting under Missing at Random
Yonghyun Kwon, Jae Kwang Kim, Yumou Qiu
We propose a unified class of calibration weighting methods based on weighted generalized entropy to handle missing at random (MAR) data with improved stability and efficiency. The…
Generalized entropy calibration for analyzing voluntary survey data
Yonghyun Kwon, Jae Kwang Kim, Yumou Qiu
Statistical analysis of voluntary survey data is an important area of research in survey sampling. We consider a unified approach to voluntary survey data analysis under the assump…
Debiased calibration estimation using generalized entropy in survey sampling
Yonghyun Kwon, Jae Kwang Kim, Yumou Qiu
Incorporating the auxiliary information into the survey estimation is a fundamental problem in survey sampling. Calibration weighting is a popular tool for incorporating the auxili…