4 citations · 9 across the 15 of their papers we have counts for
18 papers
Robust Weighted Triangulation of Causal Effects Under Model Uncertainty
Rohit Bhattacharya, Ina Ocelli, Ted Westling
A fundamental challenge in causal inference with observational data is correct specification of a causal model. When there is model uncertainty, analysts may seek to use estimates…
Nonparametric Sensitivity Analysis for Unobserved Confounding with Survival Outcomes
Rui Hu, Ted Westling
In observational studies, the observed association between an exposure and outcome of interest may be distorted by unobserved confounding. Causal sensitivity analysis can be used t…
Consistency of the bootstrap for asymptotically linear estimators based on machine learning
Zhou Tang, Ted Westling
The bootstrap is a popular method of constructing confidence intervals due to its ease of use and broad applicability. Theoretical properties of bootstrap procedures have been esta…
Doubly robust estimation and inference for a log-concave counterfactual density
Daeyoung Ham, Ted Westling, Charles R. Doss
We consider the problem of causal inference based on observational data (or the related missing data problem) with a binary or discrete treatment variable. In that context, we stud…
Statistical and Causal Robustness for Causal Null Hypothesis Tests
Junhui Yang, Rohit Bhattacharya, Youjin Lee +1
Prior work applying semiparametric theory to causal inference has primarily focused on deriving estimators that exhibit statistical robustness under a prespecified causal model tha…
Nonparametric Assessment of Variable Selection and Ranking Algorithms
Zhou Tang, Ted Westling
Selecting from or ranking a set of candidates variables in terms of their capacity for predicting an outcome of interest is an important task in many scientific fields. A variety o…
Debiased inference for a covariate-adjusted regression function
Kenta Takatsu, Ted Westling
In this article, we study nonparametric inference for a covariate-adjusted regression function. This parameter captures the average association between a continuous exposure and an…
Nonparametric identification of causal effects in clustered observational studies with differential selection
Ting Ye, Ted Westling, Lindsay Page +1
The clustered observational study (COS) design is the observational study counterpart to the clustered randomized trial. In a COS, a treatment is assigned to intact groups, and all…
Nonparametric inference under a monotone hazard ratio order
Yujian Wu, Ted Westling
The ratio of the hazard functions of two populations or two strata of a single population plays an important role in time-to-event analysis. Cox regression is commonly used to esti…
Inference for treatment-specific survival curves using machine learning
Ted Westling, Alex Luedtke, Peter Gilbert +1
In the absence of data from a randomized trial, researchers often aim to use observational data to draw causal inference about the effect of a treatment on a time-to-event outcome.…
Nonparametric tests of the causal null with non-discrete exposures
Ted Westling
In many scientific studies, it is of interest to determine whether an exposure has a causal effect on an outcome. In observational studies, this is a challenging task due to the pr…
Nonparametric maximum likelihood estimation under a likelihood ratio order
Ted Westling, Kevin J. Downes, Dylan S. Small
Comparison of two univariate distributions based on independent samples from them is a fundamental problem in statistics, with applications in a wide variety of scientific discipli…
Correcting an estimator of a multivariate monotone function with isotonic regression
Ted Westling, Mark van der Laan, Marco Carone
In many problems, a sensible estimator of a possibly multivariate monotone function may itself fail to be monotone. We study the correction of such an estimator obtained via projec…
Causal isotonic regression
Ted Westling, Peter Gilbert, Marco Carone
In observational studies, potential confounders may distort the causal relationship between an exposure and an outcome. However, under some conditions, a causal dose-response curve…
Modeling the social media relationships of Irish politicians using a generalized latent space stochastic blockmodel
Tin Lok James Ng, Thomas Brendan Murphy, Ted Westling +2
Dáil Éireann is the principal chamber of the Irish parliament. The 31st Dáil Éireann is the principal chamber of the Irish parliament. The 31st Dáil was in session from March 11th,…
A unified study of nonparametric inference for monotone functions
Ted Westling, Marco Carone
The problem of nonparametric inference on a monotone function has been extensively studied in many particular cases. Estimators considered have often been of so-called Grenander ty…
Multiresolution network models
Bailey K. Fosdick, Tyler H. McCormick, Thomas Brendan Murphy +2
Many existing statistical and machine learning tools for social network analysis focus on a single level of analysis. Methods designed for clustering optimize a global partition of…
Beyond prediction: A framework for inference with variational approximations in mixture models
Ted Westling, Tyler H. McCormick
Variational inference is a popular method for estimating model parameters and conditional distributions in hierarchical and mixed models, which arise frequently in many settings in…