203 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- E. T. Tchetgen Tchetgen8 · h 47
- M. J. van der Laan2 profiles6 · h 64
- T. Cai2 profiles6 · h 70
- J. Robins5 · h 115
- Daniela M. Witten2 profiles4 · h 46
- P. Hoff4 · h 36
- R. Mukherjee4 · h 23
- T. VanderWeele4 · h 104
- Anna Neufeld2 profiles3 · h 7
- A. Shojaie3 · h 37
- A. Volfovsky3 · h 16
- D. Spiegelman2 profiles3 · h 162
- Harvard UniversityUS35 papers
- University of WashingtonUS23 papers
- University of California, BerkeleyUS8 papers
- Fred Hutch Cancer CenterUS7 papers
- University of PennsylvaniaUS7 papers
- Stanford UniversityUS4 papers
- Boston UniversityUS3 papers
- Brigham and Women's HospitalUS3 papers
- Columbia UniversityUS3 papers
- Dana-Farber Cancer InstituteUS3 papers
- Hebrew University of JerusalemIL3 papers
- National Institutes of HealthUS3 papers
13 papers · 1 filter
On Efficiency of the Plug-in Principle for Estimating Smooth Integrated Functionals of a Nonincreasing Density
Rajarshi Mukherjee, Bodhisattva Sen
We consider the problem of estimating smooth integrated functionals of a monotone nonincreasing density on using the nonparametric maximum likelihood based plug-in…
Testing Degree Corrections in Stochastic Block Models
Rajarshi Mukherjee, Subhabrata Sen
We study sharp detection thresholds for degree corrections in Stochastic Block Models in the context of a goodness of fit problem, and explore the effect of the unknown community a…
Adaptive Estimation of Nonparametric Functionals
Lin Liu, Rajarshi Mukherjee, James Robins +1
We provide general adaptive upper bounds for estimating nonparametric functionals based on second order U-statistics arising from finite dimensional approximation of the infinite d…
The Differential Geometry of Homogeneity Spaces Across Effect Scales
Peng Ding, Tyler J. VanderWeele
If an effect measure is more homogeneous than others, then its value is more likely to be stable across different subgroups or subpopulations. Therefore, it is of great importance…
On Varieties of Doubly Robust Estimators Under Missingness Not at Random With a Shadow Variable
Wang Miao, Eric Tchetgen Tchetgen
Suppose we are interested in the mean of an outcome variable missing not at random. Suppose however that one has available a fully observed shadow variable, which is associated wit…
Lepski's Method and Adaptive Estimation of Nonlinear Integral Functionals of Density
Rajarshi Mukherjee, Eric Tchetgen Tchetgen, James Robins
We study the adaptive minimax estimation of non-linear integral functionals of a density and extend the results obtained for linear and quadratic functionals to general functionals…
Sensitivity Analysis Without Assumptions
Peng Ding, Tyler VanderWeele
Unmeasured confounding may undermine the validity of causal inference with observational studies. Sensitivity analysis provides an attractive way to partially circumvent this issue…
Non-Local Priors for High-Dimensional Estimation
David Rossell, Donatello Telesca
Simultaneously achieving parsimony and good predictive power in high dimensions is a main challenge in statistics. Non-local priors (NLPs) possess appealing properties for high-dim…
Testing for nodal dependence in relational data matrices
Alexander Volfovsky, Peter D. Hoff
Relational data are often represented as a square matrix, the entries of which record the relationships between pairs of objects. Many statistical methods for the analysis of such…
Asymptotic theory for the semiparametric accelerated failure time model with missing data
Bin Nan, John D. Kalbfleisch, Menggang Yu
We consider a class of doubly weighted rank-based estimating methods for the transformation (or accelerated failure time) model with missing data as arise, for example, in case-coh…
Minimal sufficient causation and directed acyclic graphs
Tyler J. VanderWeele, James M. Robins
Notions of minimal sufficient causation are incorporated within the directed acyclic graph causal framework. Doing so allows for the graphical representation of sufficient causes a…
Higher order influence functions and minimax estimation of nonlinear functionals
James Robins, Lingling Li, Eric Tchetgen +1
We present a theory of point and interval estimation for nonlinear functionals in parametric, semi-, and non-parametric models based on higher order influence functions (Robins (20…
Causal inference in longitudinal studies with history-restricted marginal structural models
Romain Neugebauer, Mark J. van der Laan, Marshall M. Joffe +1
A new class of Marginal Structural Models (MSMs), History-Restricted MSMs (HRMSMs), was recently introduced for longitudinal data for the purpose of defining causal parameters whic…