Saved in:
| Main Authors: | Gelman, Andrew, Krefman, Amy, Kennedy, Lauren, Hullman, Jessica |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.08421 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Model validation for aggregate inferences in out-of-sample prediction
by: Kennedy, Lauren, et al.
Published: (2023)
by: Kennedy, Lauren, et al.
Published: (2023)
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
by: Kuh, Swen, et al.
Published: (2026)
by: Kuh, Swen, et al.
Published: (2026)
The ladder of abstraction in statistical graphics
by: Gelman, Andrew
Published: (2025)
by: Gelman, Andrew
Published: (2025)
Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
by: Gelman, Andrew, et al.
Published: (2019)
by: Gelman, Andrew, et al.
Published: (2019)
A calibrated BISG for inferring race from surname and geolocation
by: Greengard, Philip, et al.
Published: (2023)
by: Greengard, Philip, et al.
Published: (2023)
Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction with Proxy Outcomes
by: Mikhaeil, Jonas, et al.
Published: (2024)
by: Mikhaeil, Jonas, et al.
Published: (2024)
Efficient scenario analysis in real-time Bayesian election forecasting via sequential meta-posterior sampling
by: Han, Geonhee, et al.
Published: (2025)
by: Han, Geonhee, et al.
Published: (2025)
Confidences in Hypotheses
by: Bornholt, Graham N.
Published: (2021)
by: Bornholt, Graham N.
Published: (2021)
Approximate posterior recalibration
by: Cai, Tiffany, et al.
Published: (2026)
by: Cai, Tiffany, et al.
Published: (2026)
Testing Imprecise Hypotheses
by: Kania, Lucas, et al.
Published: (2025)
by: Kania, Lucas, et al.
Published: (2025)
General measures of effect size to calculate power and sample size for Wald tests with generalized linear models
by: Cochran, Amy L, et al.
Published: (2025)
by: Cochran, Amy L, et al.
Published: (2025)
Pareto Smoothed Importance Sampling
by: Vehtari, Aki, et al.
Published: (2015)
by: Vehtari, Aki, et al.
Published: (2015)
PROTEST: Nonparametric Testing of Hypotheses Enhanced by Experts' Utility Judgements
by: Lassance, Rodrigo F. L., et al.
Published: (2024)
by: Lassance, Rodrigo F. L., et al.
Published: (2024)
Multiple Testing of One-Sided Hypotheses with Conservative $p$-values
by: Seo, Kwangok, et al.
Published: (2025)
by: Seo, Kwangok, et al.
Published: (2025)
Testing Hypotheses of Covariate Effects on Topics of Discourse
by: Phelan, Gabriel, et al.
Published: (2025)
by: Phelan, Gabriel, et al.
Published: (2025)
Context-stratified Mendelian randomization: exploiting regional exposure variation to explore causal effect heterogeneity and non-linearity
by: Burgess, Stephen, et al.
Published: (2025)
by: Burgess, Stephen, et al.
Published: (2025)
Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity
by: Gang, Bowen, et al.
Published: (2023)
by: Gang, Bowen, et al.
Published: (2023)
Signal Detection under Composite Hypotheses with Identical Distributions for Signals and for Noises
by: Xing, Yiming, et al.
Published: (2025)
by: Xing, Yiming, et al.
Published: (2025)
Nested $\hat R$: Assessing the convergence of Markov chain Monte Carlo when running many short chains
by: Margossian, Charles C., et al.
Published: (2021)
by: Margossian, Charles C., et al.
Published: (2021)
Improving Survey Inference in Two-phase Designs Using Bayesian Machine Learning
by: Wang, Xinru, et al.
Published: (2023)
by: Wang, Xinru, et al.
Published: (2023)
Bayesian cross-validation by parallel Markov Chain Monte Carlo
by: Cooper, Alex, et al.
Published: (2023)
by: Cooper, Alex, et al.
Published: (2023)
Asymptotics in Multiple Hypotheses Testing under Dependence: beyond Normality
by: Dey, Monitirtha
Published: (2024)
by: Dey, Monitirtha
Published: (2024)
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
by: Ham, Dae Woong, et al.
Published: (2022)
by: Ham, Dae Woong, et al.
Published: (2022)
Detecting Where Effects Occur by Testing Hypotheses in Order
by: Bowers, Jake, et al.
Published: (2026)
by: Bowers, Jake, et al.
Published: (2026)
Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
by: Li, Changjun, et al.
Published: (2026)
by: Li, Changjun, et al.
Published: (2026)
A Change-Point Approach to Estimating the Proportion of False Null Hypotheses in Multiple Testing
by: Kostic, Anica, et al.
Published: (2023)
by: Kostic, Anica, et al.
Published: (2023)
Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity
by: Modrák, Martin, et al.
Published: (2022)
by: Modrák, Martin, et al.
Published: (2022)
Sample size calculations for multilevel factorial longitudinal cluster randomised trials
by: Bowden, Rhys, et al.
Published: (2025)
by: Bowden, Rhys, et al.
Published: (2025)
Multiple Testing of Partial Conjunction Hypotheses for Assessing Replicability Across Dependent Studies
by: Dey, Monitirtha, et al.
Published: (2025)
by: Dey, Monitirtha, et al.
Published: (2025)
Compositional Covariate Importance Testing via Partial Conjunction of Bivariate Hypotheses
by: Bhaduri, Ritwik, et al.
Published: (2024)
by: Bhaduri, Ritwik, et al.
Published: (2024)
Modified Tests of Linear Hypotheses Under Heteroscedasticity for Multivariate Functional Data with Finite Sample Sizes
by: Zhu, Tianming
Published: (2025)
by: Zhu, Tianming
Published: (2025)
Sensitivity analysis for incremental effects, with application to a study of victimization & offending
by: Shen, Shuying, et al.
Published: (2026)
by: Shen, Shuying, et al.
Published: (2026)
Intervention effects based on potential benefit
by: Levis, Alexander W., et al.
Published: (2024)
by: Levis, Alexander W., et al.
Published: (2024)
Conformal Prediction and Human Decision Making
by: Hullman, Jessica, et al.
Published: (2025)
by: Hullman, Jessica, et al.
Published: (2025)
Nonparametric identification and efficient estimation of causal effects with instrumental variables
by: Levis, Alexander W., et al.
Published: (2024)
by: Levis, Alexander W., et al.
Published: (2024)
Testing Hypotheses regarding Covariance and Correlation matrices with the R package CovCorTest
by: Sattler, Paavo, et al.
Published: (2025)
by: Sattler, Paavo, et al.
Published: (2025)
Effective sample size: a measure of individual uncertainty in predictions
by: Thomassen, Doranne, et al.
Published: (2023)
by: Thomassen, Doranne, et al.
Published: (2023)
Incremental effects for continuous exposures
by: Schindl, Kyle, et al.
Published: (2024)
by: Schindl, Kyle, et al.
Published: (2024)
Non-parametric assessment of the calibration of individualized treatment effects
by: Sadatsafavi, Mohsen, et al.
Published: (2025)
by: Sadatsafavi, Mohsen, et al.
Published: (2025)
Causal effects based on distributional distances
by: Kim, Kwangho, et al.
Published: (2018)
by: Kim, Kwangho, et al.
Published: (2018)
Similar Items
-
Model validation for aggregate inferences in out-of-sample prediction
by: Kennedy, Lauren, et al.
Published: (2023) -
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
by: Kuh, Swen, et al.
Published: (2026) -
The ladder of abstraction in statistical graphics
by: Gelman, Andrew
Published: (2025) -
Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
by: Gelman, Andrew, et al.
Published: (2019) -
A calibrated BISG for inferring race from surname and geolocation
by: Greengard, Philip, et al.
Published: (2023)