Imagen de Portada

Design-Based Ratio Estimators and Central Limit Theorems for Clustered, Blocked RCTs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Schochet, Peter Z., Pashley, Nicole E., Miratrix, Luke W., Kautz, Tim
Formato:	Preprint
Publicado:	2020
Materias:	Methodology
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Design-Based Estimation and Central Limit Theorems for Local Average Treatment Effects for RCTs
por: Schochet, Peter Z
Publicado: (2024)

Insights on Variance Estimation for Blocked and Matched Pairs Designs
por: Pashley, Nicole E., et al.
Publicado: (2017)

Stratified Sampling for Model-Assisted Estimation with Surrogate Outcomes
por: Mozer, Reagan, et al.
Publicado: (2026)

Improving instrumental variable estimators with post-stratification
por: Pashley, Nicole E., et al.
Publicado: (2023)

Design-based Causal Inference for Incomplete Block Designs
por: Koo, Taehyeon, et al.
Publicado: (2024)

Note on the Delta Method for Finite Population Inference with Applications to Causal Inference
por: Pashley, Nicole E.
Publicado: (2019)

More power to you: Using machine learning to augment human coding for more efficient inference in text-based randomized trials
por: Mozer, Reagan, et al.
Publicado: (2023)

Multilevel Metamodels: Enhancing Inference, Interpretability, and Generalizability in Monte Carlo Simulation Studies
por: Gilbert, Joshua, et al.
Publicado: (2024)

Estimating Heterogeneous Causal Effects of High-Dimensional Treatments: Application to Conjoint Analysis
por: Goplerud, Max, et al.
Publicado: (2022)

Bounds on causal effects in $2^{K}$ factorial experiments with non-compliance
por: Blackwell, Matthew, et al.
Publicado: (2024)

Benefits and costs of matching prior to a Difference in Differences analysis when parallel trends does not hold
por: Ham, Dae Woong, et al.
Publicado: (2022)

Caliper Synthetic Matching: Generalized Radius Matching with Local Synthetic Controls
por: Che, Jonathan, et al.
Publicado: (2024)

Sequential Sensitivity Analysis for Multiple Assumptions: A Framework for Understanding Racial Disparity in Police Use of Force
por: Leavitt, Thomas, et al.
Publicado: (2026)

Variance estimation after matching or re-weighting
por: Meng, Xiang, et al.
Publicado: (2025)

Analysis and sample-size determination for $2^K$ audit experiments with binary response and application to identification of effect of racial discrimination on access to justice
por: Pashley, Nicole, et al.
Publicado: (2025)

Improving the Estimation of Site-Specific Effects and their Distribution in Multisite Trials
por: Lee, JoonHo, et al.
Publicado: (2023)

Optimal allocation of sample size for randomization-based inference from $2^K$ factorial designs
por: Ravichandran, Arun, et al.
Publicado: (2023)

Assessing the replicability of RCTs in RWE emulations
por: Köppe, Jeanette, et al.
Publicado: (2024)

Leveraging text data for causal inference using electronic health records
por: Mozer, Reagan, et al.
Publicado: (2023)

Augmenting Limited and Biased RCTs through Pseudo-Sample Matching-Based Observational Data Fusion Method
por: Han, Kairong, et al.
Publicado: (2025)

General Covariance-Based Conditions for Central Limit Theorems with Dependent Triangular Arrays
por: Chandrasekhar, Arun G., et al.
Publicado: (2023)

Design of Bayesian Clinical Trials with Clustered Data
por: Hagar, Luke, et al.
Publicado: (2025)

A General Framework for Design-Based Treatment Effect Estimation in Paired Cluster-Randomized Experiments
por: Mann, Charlotte Z., et al.
Publicado: (2024)

Powering RCTs for marginal effects with GLMs using prognostic score adjustment
por: Højbjerre-Frandsen, Emilie, et al.
Publicado: (2025)

Impact of Non-Informative Censoring on Propensity Score Based Estimation of Marginal Hazard Ratios
por: Barros, Guilherme W. F., et al.
Publicado: (2024)

Outcomes truncated by death in RCTs: a simulation study on the survivor average causal effect
por: von Felten, Stefanie, et al.
Publicado: (2023)

Group Sequential Methods for the Win Ratio
por: Bergemann, Tracy, et al.
Publicado: (2026)

The Deep Latent Position Block Model For The Block Clustering And Latent Representation Of Networks
por: Boutin, Rémi, et al.
Publicado: (2024)

Integrating RCTs, RWD, AI/ML and Statistics: Next-Generation Evidence Synthesis
por: Yang, Shu, et al.
Publicado: (2025)

Reinforcing RCTs with Multiple Priors while Learning about External Validity
por: Finan, Frederico, et al.
Publicado: (2021)

Estimating Treatment and Spillover Effects with the Ego-Cluster Experimental Design
por: Liu, Xiao, et al.
Publicado: (2026)

Linear Regression: Inference Based on Cluster Estimates
por: Dey, Subhodeep, et al.
Publicado: (2026)

Efficient Input Uncertainty Quantification for Ratio Estimator
por: He, Linyun, et al.
Publicado: (2024)

Limit Theorems for Network Dependent Random Variables
por: Kojevnikov, Denis, et al.
Publicado: (2019)

Evaluating virtual-control-augmented trials for reproducing treatment effect from original RCTs
por: Fernandes, Alex, et al.
Publicado: (2025)

The Win Ratio at the Design Stage of Clinical Trials
por: Kronthaler, David, et al.
Publicado: (2025)

Stochastic Block Covariance Matrix Estimation
por: Chen, Yunran, et al.
Publicado: (2025)

Co-Clustering Multi-View Data Using the Latent Block Model
por: Tobin, Joshua, et al.
Publicado: (2024)

Quantifying Treatment Effects: Estimating Risk Ratios in Causal Inference
por: Boughdiri, Ahmed, et al.
Publicado: (2024)

Projection Pursuit Density Ratio Estimation
por: Wang, Meilin, et al.
Publicado: (2025)