5 papers
Toward a Semiparametric Efficiency Theory under Equality Constraints in Nested Markov Models
Razieh Nabi, Anna Guo, Lin Liu
Probabilistic models of Directed Acyclic Graphs (DAGs) with latent variables impose equality constraints on the observed data distribution beyond ordinary conditional independencie…
Weighting-Based Identification and Estimation in Graphical Models of Missing Data
Anna Guo, Razieh Nabi
We propose a constructive algorithm for identifying complete data distributions in graphical models of missing data. The complete data distribution is unrestricted, while the missi…
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…
Average Causal Effect Estimation in DAGs with Hidden Variables: Beyond Back-Door and Front-Door Criteria
Anna Guo, Razieh Nabi
The identification theory for causal effects in directed acyclic graphs (DAGs) with hidden variables is well established, but methods for estimating and inferring functionals that…
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…