arXiv (All)
open access
Targeted Function Balancing: Flexible balancing weights that leverage strategic imbalance to estimate causal effects
When estimating the average treatment effect of a binary intervention with weights, investigators are often burdened with how best to leave imbalance in the distributions of observed covariates. This requires that investigators proceed cautiously, as imbalance in key (nonlinear transformations of) c
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Multi-dimensional Bias in Modeling Multi-dimensional Preferences: Evaluating the Ability of Synthetic Agents to Replace Human Participants in Conjoint Experiments#927544
- Higher-Order Mean-Field Control Barrier Functions#1118925
- Accounting for Bias Enables Sustainable LLM Evaluation#1105742
- Designing a Federal Parliamentary System with Minimal Manipulation: A Quantitative Systems Framework of Balance, Feedback, and Institutional Integrity#728777
- BiAxisBias: Evaluating LLM Bias Beyond a Single Prompt and a Single Explanation#618062
Record · ID 1034622
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive