2 citations · 3 across the 3 of their papers we have counts for
3 papers
stat.ME2023★ 1 cited
Multiple bias-calibration for adjusting selection bias of non-probability samples using data integration
Zhonglei Wang, Shu Yang, Jae Kwang Kim
Valid statistical inference is challenging when the sample is subject to unknown selection bias. Data integration can be used to correct for selection bias when we have a parallel…
stat.ME2022★ 2 cited
Semiparametric imputation using latent sparse conditional Gaussian mixtures for multivariate mixed outcomes
Shonosuke Sugasawa, Jae Kwang Kim, Kosuke Morikawa
This paper proposes a flexible Bayesian approach to multiple imputation using conditional Gaussian mixtures. We introduce novel shrinkage priors for covariate-dependent mixing prop…
stat.ME2022
Maximum Likelihood Imputation
Jeongseop Han, Youngjo Lee, Jae Kwang Kim
Maximum likelihood (ML) estimation is widely used in statistics. The h-likelihood has been proposed as an extension of Fisher's likelihood to statistical models including unobserve…