SelectedWorks - Jae Kwang Kim

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Selected Works of Jae Kwang Kim

Professor of Statistics

I am a professor in Statistics department at Iowa State University (ISU) and also a professor in Department of Mathematical Sciences at KAIST in Korea. I got my PhD in Statistics from Iowa State University under the supervision of professor Wayne A. Fuller in the summer of 2000.

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About Jae Kwang Kim

I am a professor in Statistics department at Iowa State University (ISU) and also a professor in Department of Mathematical Sciences at KAIST in Korea. I got my PhD in Statistics from Iowa State University under the supervision of professor Wayne A. Fuller in the summer of 2000.

Present	Professor of Statistics, Iowa State University
Institution Organization Position Type Position Title Time Period to Options Current Position Affiliate my profile with this Institution

Statistics and Probability

Survey Sampling, Statistical Analysis with missing data, Measurement error models, Multi-level models, Causal Inference, Statistical Computing, Bayesian inference, Prediction with big data, etc.

Articles in Refereed Journals (52)

Asymptotic theory and inference of predictive mean matching imputation using ...

Scandinavian Journal of Statistics (2020)

Shu Yang and Jae Kwang Kim

Predictive mean matching imputation is popular for handling item nonresponse in survey sampling. In this article, we study the asymptotic ...

Do we need to reconsider the CMAM admission and discharge ...

BMC Public Health (2020)

Eunyong Ahn, Cyprian Ouma, Mesfin Loha, Asrat Dibaba, et al.

Background: Weight-for-height Z-score (WHZ) and Mid Upper Arm Circumference (MUAC) are both commonly used as acute malnutrition screening criteria. However, ...

Doubly Robust Inference when Combining Probability and Non-probability Samples with ...

Journal of the Royal Statistical Society: Series B (2020)

Shu Yang, Jae Kwang Kim and Rui Song

Non-probability samples become increasingly popular in survey statistics but may suffer from selection biases that limit the generalizability of results ...

Accounting for model uncertainty in multiple imputation under complex sampling

Scandinavian Journal of Statistics (2020)

Gyuhyeong Goh and Jae Kwang Kim

Multiple imputation provides an effective way to handle missing data. When several possible models are under consideration for the data, ...

Semiparametric fractional imputation using Gaussian mixture models for handling multivariate ...

Journal of the American Statistical Association (2020)

Hejian Sang, Jae Kwang Kim and Danhyang Lee

Item nonresponse is frequently encountered in practice. Ignoring missing data can lose efficiency and lead to misleading inference. Fractional imputation ...

Variance estimation after Kernel Ridge Regression Imputation

Statistics Conference Proceedings, Presentations and Posters (2020)

Hengfang Wang and Jae Kwang Kim

Imputation is a popular technique for handling missing data. Variance estimation after imputation is an important practical problem in statistics. ...

A note on propensity score weighting method using paradata in ...

Survey Methodology (2019)

Seho Park, Jae Kwang Kim and Kimin Kim

Paradata is often collected during the survey process to monitor the quality of the survey response. One such paradata is ...

Sampling Techniques for Big Data Analysis

International Statistical Review (2019)

Jae Kwang Kim and Zhonglei Wang

In analysing big data for finite population inference, it is critical to adjust for the selection bias in the big ...

Mass imputation for two-phase sampling

Journal of the Korean Statistical Society (2019)

Seho Park and Jae Kwang Kim

Two-phase sampling is a cost-effective method of data collection using outcomedependent sampling for the second-phase sample. In order to make ...

Contribution to Book

Nearest Neighbor Imputation for General Parameter Estimation in Survey Sampling

The Econometrics of Complex Survey Data: Theory and Applications (2019)

Shu Yang and Jae Kwang Kim

Nearest neighbor imputation has a long tradition for handling item nonresponse in survey sampling. In this article, we study the ...

A robust calibration-assisted method for linear mixed effects model under ...

Statistica Sinica (2018)

Yongchan Kwon, Jae Kwang Kim, Myunghee Cho Paik and Hongsoo Kim

We propose a method for linear mixed effects models when the covariates are completely observed but the outcome of interest ...

Estimation of area under the ROC curve under nonignorable verification ...

Statistica Sinica (2018)

Wenbao Yu, Jae Kwang Kim and Taesung Park

The Area Under the Receiving Operating Characteristic Curve (AUC) is frequently used for assessing the overall accuracy of a diagnostic ...

Combining Survey and Non-survey Data for Improved Sub-area Prediction Using ...

Journal of Agricultural, Biological, and Environmental Statistics (2018)

Jae Kwang Kim, Zhonglei Wang, Zhengyuan Zhu and Nathan B. Cruze

Combining information from different sources is an important practical problem in survey sampling. Using a hierarchical area-level model, we establish ...

A Random Effect Model Approach to Survey Data Integration

Statistics and Applications (2018)

Eunseon Gwak, Jae Kwang Kim and Youngwon Kim

Combining information from several surveys, or survey integration, is an important practical problem in survey sampling. When the samples are ...

Bottom-up estimation and top-down prediction: Solar energy prediction combining information ...

The Annals of Applied Statistics (2018)

Youngdeok Hwang, Siyuan Lu and Jae Kwang Kim

Accurately forecasting solar power using the data from multiple sources is an important but challenging problem. Our goal is to ...

Discussion of ”Dissecting multiple imputation from a multi-phase inference perspective ...

Statistica Sinica (2017)

Shu Yang and Jae Kwang Kim

We would like to first congratulate Drs. Xie and Meng on their excellent work on investigating the mystery of multiple ...

Semiparametric fractional imputation using empirical likelihood in survey sampling

Statistical Theory and Related Fields (2017)

Sixia Chen and Jae Kwang Kim

The empirical likelihood method is a powerful tool for incorporating moment conditions in statistical inference. We propose a novel application ...

A semiparametric inference to regression analysis with missing covariates in ...

Statistica Sinica (2017)

Shu Yang and Jae Kwang Kim

Parameter estimation in parametric regression models with missing covariates is considered under a survey sampling setup. Under missingness at random, ...

A note on regression estimation with unknown population size

Survey Methodology (2016)

Michael A. Hidiroglou, Jae Kwang Kim and Christian Olivier Nambeu

The regression estimator is extensively used in practice because it can improve the reliability of the estimated parameters of interest ...

Statistical matching using fractional imputation

Survey Methodology (2016)

Jae Kwang Kim, Emily J. Berg and Taesung Park

Statistical matching is a technique for integrating two or more data sets when information available for matching records for individual ...

A note on multiple imputation for method of moments estimation

Biometrika (2016)

Shu Yang and Jae Kwang Kim

Multiple imputation is widely used for estimation in situations where there are missing data. Rubin (1987) provided an easily applicable ...

An imputation approach for handling mixed-mode surveys

The Annals of Applied Statistics (2016)

Seunghwan Park, Jae Kwang Kim and Sangun Park

Mixed-mode surveys are becoming more popular recently because of their convenience for users, but different mode effects can complicate the ...

Fractional Imputation in Survey Sampling: A Comparative Review

Statistical Science (2016)

Shu Yang and Jae Kwang Kim

Fractional imputation (FI) is a relatively new method of imputation for handling item nonresponse in survey sampling. In FI, several ...

Factors Associated with Parent Concern for Child Weight and Parenting ...

Childhood Obesity (2015)

Karissa L. Preyer, Gregory Welk, Geisinger Health System, Shu Yang, et al.

Background: A parent's perception about their child's overweight status is an important precursor or determinant of preventative actions. Acknowledgment of, ...

Small area estimation combining information from several sources

Survey Methodology (2015)

Jae Kwang Kim, Seunghwan Park and Seo-young Kim

An area-level model approach to combining information from several sources is considered in the context of small area estimation. At ...