Front-Door Versus Back-Door Adjustment With Unmeasured Confounding: Bias Formulas for Front-Door and Hybrid Adjustments With Application to a Job Training Program
From MaRDI portal
Publication:4559691
DOI10.1080/01621459.2017.1398657zbMath1402.62270OpenAlexW2779135360MaRDI QIDQ4559691
Konstantin Kashin, Adam N. Glynn
Publication date: 4 December 2018
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/01621459.2017.1398657
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Analytic bounds on causal risk differences in directed acyclic graphs involving three observed binary variables
- A simple test for the ignorability of non-compliance in experiments
- Using Information on Realized Effects to Determine Prospective Causal Effects
- Identification of Causal Effects Using Instrumental Variables
- Training, Wages, and Sample Selection: Estimating Sharp Bounds on Treatment Effects
- The Sign of the Bias of Unmeasured Confounding
- Causal diagrams for empirical research
- Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme
- Bounds on Treatment Effects From Studies With Imperfect Compliance
- Substitution and Dropout Bias in Social Experiments: A Study of an Influential Social Experiment
- IDENTIFIABILITY CRITERIA FOR CAUSAL EFFECTS OF JOINT INTERVENTIONS
- Characterizing Selection Bias Using Experimental Data
- Signed Directed Acyclic Graphs for Causal Inference
- Likelihood-Based Analysis of Causal Effects of Job-Training Programs Using Principal Stratification
- Instrumental Variables Estimates of the Effect of Subsidized Training on the Quantiles of Trainee Earnings
This page was built for publication: Front-Door Versus Back-Door Adjustment With Unmeasured Confounding: Bias Formulas for Front-Door and Hybrid Adjustments With Application to a Job Training Program