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07/21/2023
Multiple bias-calibration for adjusting selection bias of non-probability samples using data integration
Valid statistical inference is challenging when the sample is subject to...
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06/27/2023
Triply robust estimation under missing at random
Missing data is frequently encountered in many areas of statistics. Impu...
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11/06/2022
An empirical likelihood approach to reduce selection bias in voluntary samples
We address the weighting problem in voluntary samples under a nonignorab...
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08/16/2022
Semiparametric imputation using latent sparse conditional Gaussian mixtures for multivariate mixed outcomes
This paper proposes a flexible Bayesian approach to multiple imputation ...
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08/11/2022
Semiparametric adaptive estimation under informative sampling
In survey sampling, survey data do not necessarily represent the target ...
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07/20/2022
Maximum Likelihood Imputation
Maximum likelihood (ML) estimation is widely used in statistics. The h-l...
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06/02/2022
Soft calibration for selection bias problems under mixed-effects models
Calibration weighting has been widely used for correcting selection bias...
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04/20/2022
Functional Calibration under Non-Probability Survey Sampling
Non-probability sampling is prevailing in survey sampling, but ignoring ...
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02/23/2022
Nearest neighbor ratio imputation with incomplete multi-nomial outcome in survey sampling
Nonresponse is a common problem in survey sampling. Appropriate treatmen...
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07/15/2021
Statistical inference using Regularized M-estimation in the reproducing kernel Hilbert space for handling missing data
Imputation and propensity score weighting are two popular techniques for...
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07/14/2021
Survey data integration for regression analysis using model calibration
We consider regression analysis in the context of data integration. To c...
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04/27/2021
Propensity Score Estimation Using Density Ratio Model under Item Nonresponse
Missing data is frequently encountered in practice. Propensity score est...
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11/11/2020
Maximum sampled conditional likelihood for informative subsampling
Subsampling is a computationally effective approach to extract informati...
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01/09/2020
Statistical Data Integration in Survey Sampling: A Review
Finite population inference is a central goal in survey sampling. Probab...
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09/14/2019
Semiparametric Imputation Using Conditional Gaussian Mixture Models under Item Nonresponse
Imputation is a popular technique for handling item nonresponse in surve...
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06/11/2019
An approximate Bayesian approach to regression estimation with many auxiliary variables
Model-assisted estimation with complex survey data is an important pract...
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03/12/2019
Doubly Robust Inference when Combining Probability and Non-probability Samples with High-dimensional Data
Non-probability samples become increasingly popular in survey statistics...
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03/08/2019
Imputation estimators for unnormalized models with missing data
We propose estimation methods for unnormalized models with missing data....
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02/24/2019
Hypotheses Testing from Complex Survey Data Using Bootstrap Weights: A Unified Approach
Standard statistical methods that do not take proper account of the comp...
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01/07/2019
Bootstrap inference for the finite population total under complex sampling designs
Bootstrap is a useful tool for making statistical inference, but it may ...
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12/27/2018
Combining Non-probability and Probability Survey Samples Through Mass Imputation
This paper presents theoretical results on combining non-probability and...
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11/29/2018
Accounting for model uncertainty in multiple imputation under complex sampling
Multiple imputation provides an effective way to handle missing data. Wh...
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10/30/2018
Semiparametric response model with nonignorable nonresponse
How to deal with nonignorable response is often a challenging problem en...
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09/16/2018
Semiparametric fractional imputation using Gaussian mixture models for handling multivariate missing data
Item nonresponse is frequently encountered in practice. Ignoring missing...
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07/28/2018
Bayesian Sparse Propensity Score Estimation for Unit Nonresponse
Nonresponse weighting adjustment using propensity score is a popular met...
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07/08/2018
Integration of survey data and big observational data for finite population inference using mass imputation
Multiple data sources are becoming increasingly available for statistica...
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01/29/2018