Image de couverture de livre

Estimation of the Number Needed to Treat, the Number Needed to be Exposed, and the Exposure Impact Number with Instrumental Variables

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Vancak, Valentin, Sjölander, Arvid
Format:	Preprint
Publié:	2023
Sujets:	Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Definition, Identification, and Estimation of the Direct and Indirect Number Needed to Treat
par: Vancak, Valentin, et autres
Publié: (2025)

Deriving Complete Constraints in Hidden Variable Models
par: Sachs, Michael C., et autres
Publié: (2026)

The impact of coarsening an exposure on partial identifiability in instrumental variable settings
par: Gabriel, Erin E., et autres
Publié: (2024)

The Effective Number of Parameters in Kernel Density Estimation
par: Guglielmini, Sofia, et autres
Publié: (2024)

Nonparametric Bounds for Evaluating the Clinical Utility of Treatment Rules
par: Hruza, Johannes, et autres
Publié: (2025)

Calibration with Bagging of the Principal Components on a Large Number of Auxiliary Variables
par: Hasler, Caren, et autres
Publié: (2025)

Debiased Estimating Equation Method for Robust and Efficient Mendelian Randomization Using a Large Number of Correlated Weak and Invalid Instruments
par: Wang, Ruoyu, et autres
Publié: (2024)

Adding covariates to bounds: What is the question?
par: Jonzon, Gustav, et autres
Publié: (2025)

A Graph-based Approach to Estimating the Number of Clusters in High-dimensional Settings
par: Bai, Yichuan, et autres
Publié: (2024)

On the limitations for causal inference in Cox models with time-varying treatment
par: Knudsen, Mark B., et autres
Publié: (2025)

Multiple Hypothesis Testing To Estimate The Number Of Communities in Stochastic Block Models
par: Jha, Chetkar, et autres
Publié: (2025)

Instrumental Variable Estimation of Distributional Causal Effects
par: Kook, Lucas, et autres
Publié: (2024)

Unlocking the Power of Time-Since-Infection Models: Data Augmentation for Improved Instantaneous Reproduction Number Estimation
par: Shi, Jiasheng, et autres
Publié: (2024)

Estimating the Number of Components in Finite Mixture Models via Variational Approximation
par: Wang, Chenyang, et autres
Publié: (2024)

Quantifying Omitted Variable Bias in Nonlinear Instrumental Variable Estimators
par: Yen, Yu-Min
Publié: (2026)

An Eigengap Ratio Test for Determining the Number of Communities in Network Data
par: Wu, Yujia, et autres
Publié: (2024)

Determining the Number of Common Functional Factors with Twice Cross-Validation
par: Jiang, Hui, et autres
Publié: (2024)

Review on Determining the Number of Communities in Network Data
par: Du, Zhengyuan, et autres
Publié: (2025)

Marginal Causal Effect Estimation with Continuous Instrumental Variables
par: Dong, Mei, et autres
Publié: (2025)

Consistent Selection of the Number of Groups in Panel Models via Cross-Validation
par: Li, Zhe, et autres
Publié: (2022)

Risk Estimate under a Time-Varying Autoregressive Model for Data-Driven Reproduction Number Estimation
par: Pascal, Barbara, et autres
Publié: (2024)

Non-parametric Replication of Instrumental Variable Estimates Across Studies
par: Zawadzki, Roy S., et autres
Publié: (2024)

Estimating the Instantaneous Reproduction Number With Imperfect Data: A Method to Account for Case-Reporting Variation and Serial Interval Uncertainty
par: Hettinger, Gary, et autres
Publié: (2023)

OPTICS: Order-Preserved Test-Inverse Confidence Set for Number of Change-Points
par: Sun, Ao, et autres
Publié: (2026)

On Doubly Robust Estimation with Nonignorable Missing Data Using Instrumental Variables
par: Sun, Baoluo, et autres
Publié: (2023)

An Instrumental Variable Estimator for Mixed Indicators: Analytic Derivatives and Alternative Parameterizations
par: Fisher, Zachary F., et autres
Publié: (2019)

Optimization of Survey Weights under a Large Number of Conflicting Constraints
par: Williams, Matthew R., et autres
Publié: (2019)

Propensity weighting plus adjustment in proportional hazards model is not doubly robust
par: Gabriel, Erin E, et autres
Publié: (2023)

Determining the Number of Communities in Sparse and Imbalanced Settings
par: Shao, Zhixuan, et autres
Publié: (2024)

The Multiplicative Instrumental Variable Model
par: Liu, Jiewen, et autres
Publié: (2025)

Selecting the Number of Communities for Weighted Degree-Corrected Stochastic Block Models
par: Liu, Yucheng, et autres
Publié: (2024)

Determine the Number of States in Hidden Markov Models via Marginal Likelihood
par: Chen, Yang, et autres
Publié: (2024)

Iterative Estimation of Nonparametric Regressions with Continuous Endogenous Variables and Discrete Instruments
par: Centorrino, Samuele, et autres
Publié: (2019)

Optimal Instrument Selection using Bayesian Model Averaging for Model Implied Instrumental Variable Two Stage Least Squares Estimators
par: Henry, Teague R., et autres
Publié: (2018)

Model Checking for Regressions Based on Weighted Residual Processes with Diverging Number of Predictors
par: Hu, Yue, et autres
Publié: (2026)

The Multiplicative Quasi-Instrumental Variable Model
par: Liu, Jiewen, et autres
Publié: (2026)

On the Number of Conditional Independence Tests in Constraint-based Causal Discovery
par: Monés, Marc Franquesa, et autres
Publié: (2026)

Correcting a Nonparametric Two-sample Graph Hypothesis Test for Graphs with Different Numbers of Vertices with Applications to Connectomics
par: Alyakin, Anton A., et autres
Publié: (2020)

Realizing Common Random Numbers: Event-Keyed Hashing for Causally Valid Stochastic Models
par: Buffalo, Vince, et autres
Publié: (2026)

Instrument, Variable and Model Selection with Nonignorable Nonresponse
par: Chen, Ji, et autres
Publié: (2025)