NP-EBCIs achieve asymptotic exact coverage for individual effects at logarithmic rates and shorten intervals in simulations compared to isolated treatment.
Sources of geographic variation in health care: Evidence from patient migration
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3verdicts
UNVERDICTED 3representative citing papers
A model-free estimator for causal effects in two-sample Mendelian randomization that is consistent and asymptotically normal under population heterogeneity between samples.
Generalization bounds can be obtained deterministically via sensitivity analysis of optimization problems, with probabilistic assumptions used ex post to bound the error term measuring closeness of out-of-sample to in-sample data.
citing papers explorer
-
Nonparametric Empirical Bayes Confidence Intervals
NP-EBCIs achieve asymptotic exact coverage for individual effects at logarithmic rates and shorten intervals in simulations compared to isolated treatment.
-
A Robust Framework for Two-Sample Mendelian Randomization under Population Heterogeneity
A model-free estimator for causal effects in two-sample Mendelian randomization that is consistent and asymptotically normal under population heterogeneity between samples.
-
Separating Geometry from Probability in the Analysis of Generalization
Generalization bounds can be obtained deterministically via sensitivity analysis of optimization problems, with probabilistic assumptions used ex post to bound the error term measuring closeness of out-of-sample to in-sample data.