Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling
Fuente:
arXiv
Guardado en:
| Autores principales: | Kim, Jooho, Shin, Yei Eun |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
BAMIFun: Bayesian Multiple Imputation for Functional Data
por: Jiang, Ziren, et al.
Publicado: (2026)
por: Jiang, Ziren, et al.
Publicado: (2026)
Multiple Imputation Diagnostics when using Electronic Health Record Data in Observational Studies: A Case Study
por: Bhavsar, Nrupen A., et al.
Publicado: (2026)
por: Bhavsar, Nrupen A., et al.
Publicado: (2026)
Compatible Imputation for Hierarchical Linear Models with Incomplete Data: Interaction Effects of Continuous and Categorical Covariates MAR
por: Shin, Dongho, et al.
Publicado: (2025)
por: Shin, Dongho, et al.
Publicado: (2025)
Outcome-Assisted Multiple Imputation of Missing Treatments
por: Feldman, Joseph, et al.
Publicado: (2025)
por: Feldman, Joseph, et al.
Publicado: (2025)
Constructing a T-test for Value Function Comparison of Individualized Treatment Regimes in the Presence of Multiple Imputation for Missing Data
por: Lu, Minxin, et al.
Publicado: (2023)
por: Lu, Minxin, et al.
Publicado: (2023)
The Role of Congeniality in Multiple Imputation for Doubly Robust Causal Estimation
por: McGowan, Lucy D'Agostino
Publicado: (2025)
por: McGowan, Lucy D'Agostino
Publicado: (2025)
Efficient Case-Cohort Design using Balanced Sampling
por: Choi, Kaeum, et al.
Publicado: (2023)
por: Choi, Kaeum, et al.
Publicado: (2023)
Multiple Imputation Method for High-Dimensional Neuroimaging Data
por: Lu, Tong, et al.
Publicado: (2023)
por: Lu, Tong, et al.
Publicado: (2023)
Multiple Imputation for Nonresponse in Complex Surveys Using Design Weights and Auxiliary Margins
por: Xu, Kewei, et al.
Publicado: (2024)
por: Xu, Kewei, et al.
Publicado: (2024)
Statistical Inference for Chi-square Statistics or F-Statistics Based on Multiple Imputation
por: Wang, Binhuan, et al.
Publicado: (2024)
por: Wang, Binhuan, et al.
Publicado: (2024)
Comparison of Parametric versus Machine-learning Multiple Imputation in Clinical Trials with Missing Continuous Outcomes
por: Tackney, Mia S., et al.
Publicado: (2025)
por: Tackney, Mia S., et al.
Publicado: (2025)
BAMITA: Bayesian Multiple Imputation for Tensor Arrays
por: Jiang, Ziren, et al.
Publicado: (2024)
por: Jiang, Ziren, et al.
Publicado: (2024)
Variational Bayesian Multiple Imputation in High-Dimensional Regression Models With Missing Responses
por: Li, Qiushuang, et al.
Publicado: (2025)
por: Li, Qiushuang, et al.
Publicado: (2025)
Temporal Wasserstein Imputation: A Versatile Method for Time Series Imputation
por: Huang, Shuo-Chieh, et al.
Publicado: (2024)
por: Huang, Shuo-Chieh, et al.
Publicado: (2024)
A Bayes-Factor-Guided Approach to Post-Double Selection with Bootstrapped Multiple Imputation
por: Bleher, Johannes, et al.
Publicado: (2026)
por: Bleher, Johannes, et al.
Publicado: (2026)
Multiple Imputation of Hierarchical Nonlinear Time Series Data with an Application to School Enrollment Data
por: Liu, Daphne H., et al.
Publicado: (2024)
por: Liu, Daphne H., et al.
Publicado: (2024)
Causal Effect Estimation on Restricted Mean Survival Time in Case-Cohort Studies via a Matching Design
por: Ni, Andy, et al.
Publicado: (2026)
por: Ni, Andy, et al.
Publicado: (2026)
Enhancing Inference for Small Cohorts via Transfer Learning and Weighted Integration of Multiple Datasets
por: Guha, Subharup, et al.
Publicado: (2025)
por: Guha, Subharup, et al.
Publicado: (2025)
A Latent Variable Framework for Multiple Imputation with Non-ignorable Missingness: Analyzing Perceptions of Social Justice in Europe
por: Zhang, Siliang, et al.
Publicado: (2025)
por: Zhang, Siliang, et al.
Publicado: (2025)
A Comparative Study of Imputation Methods for Multivariate Ordinal Data
por: Wongkamthong, Chayut, et al.
Publicado: (2020)
por: Wongkamthong, Chayut, et al.
Publicado: (2020)
Imputation-Powered Inference
por: Zhao, Sarah, et al.
Publicado: (2025)
por: Zhao, Sarah, et al.
Publicado: (2025)
Variable Selection for Linear Regression Imputation in Surveys
por: An, Ziming, et al.
Publicado: (2026)
por: An, Ziming, et al.
Publicado: (2026)
Imputation of Nonignorable Missing Data in Surveys Using Auxiliary Margins Via Hot Deck and Sequential Imputation
por: Yang, Yanjiao, et al.
Publicado: (2024)
por: Yang, Yanjiao, et al.
Publicado: (2024)
Imputation-based randomization tests for randomized experiments with interference
por: Han, Tingxuan, et al.
Publicado: (2024)
por: Han, Tingxuan, et al.
Publicado: (2024)
Bayesian Estimation of Propensity Scores for Integrating Multiple Cohorts with High-Dimensional Covariates
por: Guha, Subharup, et al.
Publicado: (2023)
por: Guha, Subharup, et al.
Publicado: (2023)
Efficient Estimation under Multiple Missing Patterns via Balancing Weights
por: Dong, Jianing, et al.
Publicado: (2025)
por: Dong, Jianing, et al.
Publicado: (2025)
A Surrogate‐Calibrated Updating Method for Logistic Regression With Missing Covariates
por: Jooha Oh, et al.
Publicado: (2026)
por: Jooha Oh, et al.
Publicado: (2026)
Automated Efficient Estimation using Monte Carlo Efficient Influence Functions
por: Agrawal, Raj, et al.
Publicado: (2024)
por: Agrawal, Raj, et al.
Publicado: (2024)
Random Indicator Imputation for Missing Not At Random Data
por: Jolani, Shahab, et al.
Publicado: (2024)
por: Jolani, Shahab, et al.
Publicado: (2024)
Design-Based Causal Inference with Missing Outcomes: Missingness Mechanisms, Imputation-Assisted Randomization Tests, and Covariate Adjustment
por: Heng, Siyu, et al.
Publicado: (2023)
por: Heng, Siyu, et al.
Publicado: (2023)
Correcting Conditional Mean Imputation for Censored Covariates and Improving Usability
por: Lotspeich, Sarah C., et al.
Publicado: (2021)
por: Lotspeich, Sarah C., et al.
Publicado: (2021)
Filtration-Based Learning of Multiscale Shared Structures for Multiple Functional Predictors
por: Jiao, Shuhao, et al.
Publicado: (2025)
por: Jiao, Shuhao, et al.
Publicado: (2025)
Sequential Hierarchical Regression Imputation with Variable Selection Routines
por: Li, Qiushuang, et al.
Publicado: (2025)
por: Li, Qiushuang, et al.
Publicado: (2025)
A Convexified Matching Approach to Imputation and Individualized Inference
por: Hur, YoonHaeng, et al.
Publicado: (2024)
por: Hur, YoonHaeng, et al.
Publicado: (2024)
Multiple Jump MCMC: A Scalable Algorithm for Bayesian Inference on Binary Model Spaces
por: Vogels, Lucas, et al.
Publicado: (2026)
por: Vogels, Lucas, et al.
Publicado: (2026)
Missing Data in Discrete Time State-Space Modeling of Ecological Momentary Assessment Data: A Monte-Carlo Study of Imputation Methods
por: Slipetz, Lindley R., et al.
Publicado: (2023)
por: Slipetz, Lindley R., et al.
Publicado: (2023)
Imputation Uncertainty in Interpretable Machine Learning Methods
por: Golchian, Pegah, et al.
Publicado: (2025)
por: Golchian, Pegah, et al.
Publicado: (2025)
Imputation of missing values in multi-view data
por: van Loon, Wouter, et al.
Publicado: (2022)
por: van Loon, Wouter, et al.
Publicado: (2022)
Robust High-Dimensional Time-Varying Coefficient Estimation
por: Shin, Minseok, et al.
Publicado: (2023)
por: Shin, Minseok, et al.
Publicado: (2023)
Nonconvex High-Dimensional Time-Varying Coefficient Estimation for Noisy High-Frequency Observations with a Factor Structure
por: Shin, Minseok, et al.
Publicado: (2024)
por: Shin, Minseok, et al.
Publicado: (2024)
Ejemplares similares
-
BAMIFun: Bayesian Multiple Imputation for Functional Data
por: Jiang, Ziren, et al.
Publicado: (2026) -
Multiple Imputation Diagnostics when using Electronic Health Record Data in Observational Studies: A Case Study
por: Bhavsar, Nrupen A., et al.
Publicado: (2026) -
Compatible Imputation for Hierarchical Linear Models with Incomplete Data: Interaction Effects of Continuous and Categorical Covariates MAR
por: Shin, Dongho, et al.
Publicado: (2025) -
Outcome-Assisted Multiple Imputation of Missing Treatments
por: Feldman, Joseph, et al.
Publicado: (2025) -
Constructing a T-test for Value Function Comparison of Individualized Treatment Regimes in the Presence of Multiple Imputation for Missing Data
por: Lu, Minxin, et al.
Publicado: (2023)