1 citations · 1 across the 3 of their papers we have counts for
16 papers
Functional Calibration under Non-Probability Survey Sampling
Zhonglei Wang, Xiaojun Mao, Jae Kwang Kim
Non-probability sampling is prevailing in survey sampling, but ignoring its selection bias leads to erroneous inferences. We offer a unified nonparametric calibration method to est…
Statistical inference using Regularized M-estimation in the reproducing kernel Hilbert space for handling missing data
Hengfang Wang, Jae Kwang Kim
Imputation and propensity score weighting are two popular techniques for handling missing data. We address these problems using the regularized M-estimation techniques in the repro…
Statistical Data Integration in Survey Sampling: A Review
Shu Yang, Jae Kwang Kim
Finite population inference is a central goal in survey sampling. Probability sampling is the main statistical approach to finite population inference. Challenges arise due to high…
Semiparametric Imputation Using Conditional Gaussian Mixture Models under Item Nonresponse
Danhyang Lee, Jae Kwang Kim
Imputation is a popular technique for handling item nonresponse in survey sampling. Parametric imputation is based on a parametric model for imputation and is less robust against t…
An Approximate Bayesian Approach to Model-assisted Survey Estimation with Many Auxiliary Variables
Shonosuke Sugasawa, Jae Kwang Kim
Model-assisted estimation with complex survey data is an important practical problem in survey sampling. When there are many auxiliary variables, selecting significant variables as…
Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data
Shu Yang, Jae Kwang Kim, Rui Song
Non-probability samples become increasingly popular in survey statistics but may suffer from selection biases that limit the generalizability of results to the target population. W…