8 citations · 28 across the 10 of their papers we have counts for
10 papers
Expert-Guided g-computation with Large Language Models for Estimating Causal Effects on Timings: Applications to Hospital Quality Improvement
Patrick Vossler, Jialin Ouyang, F. Richard Guo +5
Hospital quality improvement (QI) programs routinely face multiple candidate interventions to optimize hospital flow, but existing methods struggle to estimate and rank the causal…
The Debiased Score Test: Hunt-and-test for Semiparametric Hypotheses
Aditya Dhawan, F. Richard Guo, Rajen D. Shah
The parametric score test assesses a hypothesis through derivatives of the log-likelihood, whose expectation vanishes under the null. When the parameter of interest is a regression…
Rank-transformed subsampling: inference for multiple data splitting and exchangeable p-values
F. Richard Guo, Rajen D. Shah
Many testing problems are readily amenable to randomised tests such as those employing data splitting. However despite their usefulness in principle, randomised tests have obvious…
Confounder Selection: Objectives and Approaches
F. Richard Guo, Anton Rask Lundborg, Qingyuan Zhao
Confounder selection is perhaps the most important step in the design of observational studies. A number of criteria, often with different objectives and approaches, have been prop…
Variable elimination, graph reduction and efficient g-formula
F. Richard Guo, Emilija Perković, Andrea Rotnitzky
We study efficient estimation of an interventional mean associated with a point exposure treatment under a causal graphical model represented by a directed acyclic graph without hi…
Discussion of 'Estimating time-varying causal excursion effect in mobile health with binary outcomes' by T. Qian et al
F. Richard Guo, Thomas S. Richardson, James M. Robins
We discuss the recent paper on "excursion effect" by T. Qian et al. (2020). We show that the methods presented have close relationships to others in the literature, in particular t…
Minimal enumeration of all possible total effects in a Markov equivalence class
F. Richard Guo, Emilija Perković
In observational studies, when a total causal effect of interest is not identified, the set of all possible effects can be reported instead. This typically occurs when the underlyi…
Efficient least squares for estimating total effects under linearity and causal sufficiency
F. Richard Guo, Emilija Perković
Recursive linear structural equation models are widely used to postulate causal mechanisms underlying observational data. In these models, each variable equals a linear combination…
Chernoff-type Concentration of Empirical Probabilities in Relative Entropy
F. Richard Guo, Thomas S. Richardson
We study the relative entropy of the empirical probability vector with respect to the true probability vector in multinomial sampling of categories, which, when multiplied by s…
On Testing Marginal versus Conditional Independence
F. Richard Guo, Thomas S. Richardson
We consider testing marginal independence versus conditional independence in a trivariate Gaussian setting. The two models are non-nested and their intersection is a union of two m…