3 papers
stat.ME2025
Covariate balancing estimation and model selection for difference-in-differences approach
Takamichi Baba, Yoshiyuki Ninomiya
Remarkable progress has been made in difference-in-differences (DID) approaches to causal inference that estimate the average effect of a treatment on the treated (ATT). Of these,…
stat.ME2021
Doubly Robust Criterion for Causal Inference
Takamichi Baba, Yoshiyuki Ninomiya
The semiparametric estimation approach, which includes inverse-probability-weighted and doubly robust estimation using propensity scores, is a standard tool in causal inference, an…
stat.ME2016
criterion for semiparametric approach in causal inference
Takamichi Baba, Yoshiyuki Ninomiya
For marginal structural models, which recently play an important role in causal inference, we consider a model selection problem in the framework of a semiparametric approach using…