Imagen de Portada

Full Law Identification under Missing Data with Categorical Variables

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Tikka, Santtu, Karvanen, Juha
Formato:	Preprint
Publicado:	2024
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Monotone Missing Data: A Blessing and a Curse
por: Tikka, Santtu, et al.
Publicado: (2024)

Clustering and Pruning in Causal Data Fusion
por: Tabell, Otto, et al.
Publicado: (2025)

Do-search -- a tool for causal inference and study design with multiple data sources
por: Karvanen, Juha, et al.
Publicado: (2020)

Multiple imputation and full law identifiability
por: Karvanen, Juha, et al.
Publicado: (2024)

Identifying Causal Effects via Context-specific Independence Relations
por: Tikka, Santtu, et al.
Publicado: (2020)

Simulating counterfactuals
por: Karvanen, Juha, et al.
Publicado: (2023)

dynamite: An R Package for Dynamic Multivariate Panel Models
por: Tikka, Santtu, et al.
Publicado: (2023)

Price Optimization Combining Conjoint Data and Purchase History: A Causal Modeling Approach
por: Valkonen, Lauri, et al.
Publicado: (2023)

Bayesian subcohort selection for longitudinal covariate measurements in follow-up studies
por: Reinikainen, Jaakko, et al.
Publicado: (2016)

Dynamic programming principle in cost-efficient sequential design: application to switching measurements
por: Han, Jeongmin, et al.
Publicado: (2024)

Contrasting Identifying Assumptions of Average Causal Effects: Robustness and Semiparametric Efficiency
por: Gorbach, Tetiana, et al.
Publicado: (2021)

Complementary strengths of the Neyman-Rubin and graphical causal frameworks
por: Gorbach, Tetiana, et al.
Publicado: (2025)

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
por: Chen, Hongyu, et al.
Publicado: (2026)

A Multiplicative Instrumental Variable Model for Data Missing Not-at-Random
por: Zhang, Yunshu, et al.
Publicado: (2025)

On Doubly Robust Estimation with Nonignorable Missing Data Using Instrumental Variables
por: Sun, Baoluo, et al.
Publicado: (2023)

Categorical Data Analysis
por: Chen, Dandan, et al.
Publicado: (2024)

Semiparametric Regression Models for Explanatory Variables with Missing Data due to Detection Limit
por: Zhang, Jasen, et al.
Publicado: (2025)

Conformal Inference For Missing Data under Multiple Robust Learning
por: Tang, Wenlu, et al.
Publicado: (2025)

Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach
por: Wang, Zixiao, et al.
Publicado: (2023)

Modal Clustering for Categorical Data
por: Corsini, Noemi, et al.
Publicado: (2025)

Weighting-Based Identification and Estimation in Graphical Models of Missing Data
por: Guo, Anna, et al.
Publicado: (2026)

Robust Variable Selection for High-dimensional Regression with Missing Data and Measurement Errors
por: Zhang, Zhenhao, et al.
Publicado: (2024)

Balanced Subsampling for Big Data with Categorical Covariates
por: Wang, Lin
Publicado: (2022)

Recoverability of Causal Effects under Presence of Missing Data: a Longitudinal Case Study
por: Holovchak, Anastasiia, et al.
Publicado: (2024)

Imputing Missing Values with External Data
por: Thiesmeier, Robert, et al.
Publicado: (2024)

Balancing Weights for Non-monotone Missing Data
por: Dong, Jianing, et al.
Publicado: (2024)

Estimation of Semiparametric Factor Models with Missing Data
por: Zheng, Sijie
Publicado: (2025)

A General Approach for Calibration Weighting under Missing at Random
por: Kwon, Yonghyun, et al.
Publicado: (2025)

Robust Estimation and Inference for Categorical Data
por: Welz, Max
Publicado: (2024)

Model Uncertainty and Missing Data: An Objective Bayesian Perspective
por: García-Donato, Gonzalo, et al.
Publicado: (2024)

Adaptive Learning with Blockwise Missing and Semi-Supervised Data
por: Li, Yiming, et al.
Publicado: (2024)

A Note on Ising Network Analysis with Missing Data
por: Zhang, Siliang, et al.
Publicado: (2023)

Testing the Missing Completely at Random Assumption for Functional Data
por: Ofner, Maximilian, et al.
Publicado: (2025)

Score Matching With Missing Data
por: Givens, Josh, et al.
Publicado: (2025)

Efficient Estimation under Multiple Missing Patterns via Balancing Weights
por: Dong, Jianing, et al.
Publicado: (2025)

Hamiltonian Monte Carlo for Regression with High-Dimensional Categorical Data
por: Sacher, Szymon, et al.
Publicado: (2021)

Bayesian Causal Effect Estimation for Categorical Data using Staged Tree Models
por: Cremaschi, Andrea, et al.
Publicado: (2025)

Bayesian Unit-level Modeling of Categorical Survey Data with a Longitudinal Design
por: Vedensky, Daniel, et al.
Publicado: (2025)

A Conway-Maxwell-Multinomial Distribution for Flexible Modeling of Clustered Categorical Data
por: Morris, Darcy Steeg, et al.
Publicado: (2019)

Categorical distance correlation under general encodings and its application to high-dimensional feature screening
por: Zhang, Qingyang
Publicado: (2026)