39 citations · 107 across the 31 of their papers we have counts for
5 papers · 1 filter
Nuisance Function Tuning and Sample Splitting for Optimally Estimating a Doubly Robust Functional
Sean McGrath, Rajarshi Mukherjee
Estimators of doubly robust functionals typically rely on estimating two complex nuisance functions, such as the propensity score and conditional outcome mean for the average treat…
Sparse Signal Detection in Heteroscedastic Gaussian Sequence Models: Sharp Minimax Rates
Julien Chhor, Rajarshi Mukherjee, Subhabrata Sen
Given a heterogeneous Gaussian sequence model with unknown mean and known covariance matrix , we study the signal det…
PC Adjusted Testing for Low Dimensional Parameters
Sohom Bhattacharya, Rounak Dey, Rajarshi Mukherjee
In this paper, we investigate the impact of high-dimensional Principal Component (PC) adjustments on inferring the effects of variables on outcomes, with a focus on applications in…
A New Central Limit Theorem for the Augmented IPW Estimator: Variance Inflation, Cross-Fit Covariance and Beyond
Kuanhao Jiang, Rajarshi Mukherjee, Subhabrata Sen +1
Estimation of the average treatment effect (ATE) is a central problem in causal inference. In recent times, inference for the ATE in the presence of high-dimensional covariates has…
Double sampling for informatively missing data in electronic health record-based comparative effectiveness research
Alexander W. Levis, Rajarshi Mukherjee, Rui Wang +2
Missing data arise in most applied settings and are ubiquitous in electronic health records (EHR). When data are missing not at random (MNAR) with respect to measured covariates, s…