16 papers
Coarsening Bias from Variable Discretization in Causal Functionals
Xiaxian Ou, Razieh Nabi
Causal identification functionals often require integration over conditional densities of continuous variables, such as those arising in nonparametric identification theory of tota…
Inferring Comprehensive Cohort Causal Effects in the Presence of Unmeasured Confounding and Missing Outcomes
Shiyao Xu, Razieh Nabi, Martin Underwood +1
This paper presents a methodological framework for estimating the comprehensive cohort causal effect (CCCE) in mixed-design clinical studies that combine randomized controlled tria…
Causal Inference with the Napkin Graph
Anna Guo, Lin Liu, David Benkeser +1
Unmeasured confounding can render identification strategies based on adjustment functionals invalid. We study the "Napkin" graph, a causal structure that encapsulates features of M…
Causal Sufficient Dimension Reduction for Multiple Continuous Exposures with an Application to Environmental Mixtures
Thomas W. Hsiao, Howard H. Chang, Razieh Nabi
Estimating causal effects with multivariate continuous exposures is challenging because causal exposure-response surfaces can be high-dimensional, complicating estimation and inter…
Assessing Racial Disparities in Healthcare Expenditures via Mediator Distribution Shifts
Xiaxian Ou, Xinwei He, David Benkeser +1
Racial disparities in healthcare expenditures are well-documented, yet the underlying drivers remain complex. This study develops a framework to decompose such disparities through…
Flexible Nonparametric Inference for Causal Effects under the Front-Door Model
Anna Guo, David Benkeser, Razieh Nabi
Evaluating causal treatment effects in observational studies requires addressing confounding. While the back-door criterion enables identification through adjustment for observed c…