Hypothesizing an effect size by considering individual variation
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | Gelman, Andrew, Krefman, Amy, Kennedy, Lauren, Hullman, Jessica |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
Model validation for aggregate inferences in out-of-sample prediction
par: Kennedy, Lauren, et autres
Publié: (2023)
par: Kennedy, Lauren, et autres
Publié: (2023)
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
par: Kuh, Swen, et autres
Publié: (2026)
par: Kuh, Swen, et autres
Publié: (2026)
The ladder of abstraction in statistical graphics
par: Gelman, Andrew
Publié: (2025)
par: Gelman, Andrew
Publié: (2025)
Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
par: Gelman, Andrew, et autres
Publié: (2019)
par: Gelman, Andrew, et autres
Publié: (2019)
A calibrated BISG for inferring race from surname and geolocation
par: Greengard, Philip, et autres
Publié: (2023)
par: Greengard, Philip, et autres
Publié: (2023)
Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction with Proxy Outcomes
par: Mikhaeil, Jonas, et autres
Publié: (2024)
par: Mikhaeil, Jonas, et autres
Publié: (2024)
Confidences in Hypotheses
par: Bornholt, Graham N.
Publié: (2021)
par: Bornholt, Graham N.
Publié: (2021)
Efficient scenario analysis in real-time Bayesian election forecasting via sequential meta-posterior sampling
par: Han, Geonhee, et autres
Publié: (2025)
par: Han, Geonhee, et autres
Publié: (2025)
Testing Imprecise Hypotheses
par: Kania, Lucas, et autres
Publié: (2025)
par: Kania, Lucas, et autres
Publié: (2025)
Approximate posterior recalibration
par: Cai, Tiffany, et autres
Publié: (2026)
par: Cai, Tiffany, et autres
Publié: (2026)
General measures of effect size to calculate power and sample size for Wald tests with generalized linear models
par: Cochran, Amy L, et autres
Publié: (2025)
par: Cochran, Amy L, et autres
Publié: (2025)
PROTEST: Nonparametric Testing of Hypotheses Enhanced by Experts' Utility Judgements
par: Lassance, Rodrigo F. L., et autres
Publié: (2024)
par: Lassance, Rodrigo F. L., et autres
Publié: (2024)
Multiple Testing of One-Sided Hypotheses with Conservative $p$-values
par: Seo, Kwangok, et autres
Publié: (2025)
par: Seo, Kwangok, et autres
Publié: (2025)
Context-stratified Mendelian randomization: exploiting regional exposure variation to explore causal effect heterogeneity and non-linearity
par: Burgess, Stephen, et autres
Publié: (2025)
par: Burgess, Stephen, et autres
Publié: (2025)
Large-Scale Multiple Testing of Composite Null Hypotheses Under Heteroskedasticity
par: Gang, Bowen, et autres
Publié: (2023)
par: Gang, Bowen, et autres
Publié: (2023)
Signal Detection under Composite Hypotheses with Identical Distributions for Signals and for Noises
par: Xing, Yiming, et autres
Publié: (2025)
par: Xing, Yiming, et autres
Publié: (2025)
Testing Hypotheses of Covariate Effects on Topics of Discourse
par: Phelan, Gabriel, et autres
Publié: (2025)
par: Phelan, Gabriel, et autres
Publié: (2025)
A Change-Point Approach to Estimating the Proportion of False Null Hypotheses in Multiple Testing
par: Kostic, Anica, et autres
Publié: (2023)
par: Kostic, Anica, et autres
Publié: (2023)
Leveraging machine learning to estimate individualized treatment effects in cluster-randomized trials
par: Li, Changjun, et autres
Publié: (2026)
par: Li, Changjun, et autres
Publié: (2026)
Sample size calculations for multilevel factorial longitudinal cluster randomised trials
par: Bowden, Rhys, et autres
Publié: (2025)
par: Bowden, Rhys, et autres
Publié: (2025)
Asymptotics in Multiple Hypotheses Testing under Dependence: beyond Normality
par: Dey, Monitirtha
Publié: (2024)
par: Dey, Monitirtha
Publié: (2024)
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
par: Ham, Dae Woong, et autres
Publié: (2022)
par: Ham, Dae Woong, et autres
Publié: (2022)
Pareto Smoothed Importance Sampling
par: Vehtari, Aki, et autres
Publié: (2015)
par: Vehtari, Aki, et autres
Publié: (2015)
Improving Survey Inference in Two-phase Designs Using Bayesian Machine Learning
par: Wang, Xinru, et autres
Publié: (2023)
par: Wang, Xinru, et autres
Publié: (2023)
Bayesian cross-validation by parallel Markov Chain Monte Carlo
par: Cooper, Alex, et autres
Publié: (2023)
par: Cooper, Alex, et autres
Publié: (2023)
Modified Tests of Linear Hypotheses Under Heteroscedasticity for Multivariate Functional Data with Finite Sample Sizes
par: Zhu, Tianming
Publié: (2025)
par: Zhu, Tianming
Publié: (2025)
Multiple Testing of Partial Conjunction Hypotheses for Assessing Replicability Across Dependent Studies
par: Dey, Monitirtha, et autres
Publié: (2025)
par: Dey, Monitirtha, et autres
Publié: (2025)
Detecting Where Effects Occur by Testing Hypotheses in Order
par: Bowers, Jake, et autres
Publié: (2026)
par: Bowers, Jake, et autres
Publié: (2026)
Effective sample size: a measure of individual uncertainty in predictions
par: Thomassen, Doranne, et autres
Publié: (2023)
par: Thomassen, Doranne, et autres
Publié: (2023)
Nested $\hat R$: Assessing the convergence of Markov chain Monte Carlo when running many short chains
par: Margossian, Charles C., et autres
Publié: (2021)
par: Margossian, Charles C., et autres
Publié: (2021)
Sensitivity analysis for incremental effects, with application to a study of victimization & offending
par: Shen, Shuying, et autres
Publié: (2026)
par: Shen, Shuying, et autres
Publié: (2026)
Compositional Covariate Importance Testing via Partial Conjunction of Bivariate Hypotheses
par: Bhaduri, Ritwik, et autres
Publié: (2024)
par: Bhaduri, Ritwik, et autres
Publié: (2024)
Testing Hypotheses regarding Covariance and Correlation matrices with the R package CovCorTest
par: Sattler, Paavo, et autres
Publié: (2025)
par: Sattler, Paavo, et autres
Publié: (2025)
Intervention effects based on potential benefit
par: Levis, Alexander W., et autres
Publié: (2024)
par: Levis, Alexander W., et autres
Publié: (2024)
Nonparametric identification and efficient estimation of causal effects with instrumental variables
par: Levis, Alexander W., et autres
Publié: (2024)
par: Levis, Alexander W., et autres
Publié: (2024)
Non-parametric assessment of the calibration of individualized treatment effects
par: Sadatsafavi, Mohsen, et autres
Publié: (2025)
par: Sadatsafavi, Mohsen, et autres
Publié: (2025)
Simulation-Based Calibration Checking for Bayesian Computation: The Choice of Test Quantities Shapes Sensitivity
par: Modrák, Martin, et autres
Publié: (2022)
par: Modrák, Martin, et autres
Publié: (2022)
Incremental effects for continuous exposures
par: Schindl, Kyle, et autres
Publié: (2024)
par: Schindl, Kyle, et autres
Publié: (2024)
Causal effects based on distributional distances
par: Kim, Kwangho, et autres
Publié: (2018)
par: Kim, Kwangho, et autres
Publié: (2018)
Enhanced inference for distributions and quantiles of individual treatment effects in various experiments
par: Chen, Zhe, et autres
Publié: (2024)
par: Chen, Zhe, et autres
Publié: (2024)
Documents similaires
-
Model validation for aggregate inferences in out-of-sample prediction
par: Kennedy, Lauren, et autres
Publié: (2023) -
When Bayes goes bad: Weakly-regularized covariate adjustment leads to a biased estimate of prevalence
par: Kuh, Swen, et autres
Publié: (2026) -
The ladder of abstraction in statistical graphics
par: Gelman, Andrew
Publié: (2025) -
Slamming the sham: A Bayesian model for adaptive adjustment with noisy control data
par: Gelman, Andrew, et autres
Publié: (2019) -
A calibrated BISG for inferring race from surname and geolocation
par: Greengard, Philip, et autres
Publié: (2023)