Author

James M. Robins

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Preprint Oct 2026

Difference-in-Differences for Heterogeneous Effects of General Treatment Strategies Accounting for Time-Varying Covariates

We introduce a class of marginal Structural Nested Mean Models (mSNMMs) that enable modeling time-varying effect modification by a subset of covariates required as adjustment variables. We focus on identifiability and estimation under conditional parallel trends assumptions, so mSNMMs are applicable in settings where t...

O. Dukes, Z. Shahn, James M. Robins et al. · 0 citations

Preprint Sep 2026

Improved Variance Estimation in Homoskedastic Nonparametric Random-Design Regression via a Two-Scale Approach

We study estimation of a constant conditional variance $\sigma^2$ in nonparametric regression with a $d$-dimensional random design. This is an important problem, and similar questions arise in causal inference. The regression function is $\beta_b$-H\"older smooth, the design density is $\beta_g$-H\"older smooth and bou...

Edgar Dobriban, Rajarshi Mukherjee, James M. Robins et al. · 1 citation

#machine learning Preprint Sep 2026

Optimal Value Inference for Reinforcement Learning

Two new nuisances are derived as fixed points of a self-induced Bellman equation, in which they approximate the maximum Bellman operator by its softmax correspondence, and a debiased estimator is proposed through the Neyman orthogonality and established its asymptotic normality under diverging horizons.

Nan Lu, Ethan Lee, James M. Robins et al. · 0 citations