Gaines and Kuklinski (2011) Estimators for Hybrid Experiments
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Updated
Apr 22, 2018 - R
Gaines and Kuklinski (2011) Estimators for Hybrid Experiments
R code as supplementary material to the paper 'A novel estimand to adjust for rescue treatment in randomized clinical trials' (Michiels et al. 2021)
Outcome misclassification in a simulated randomized controlled trial
Stroke2Work analyzes return-to-work and health outcomes in stroke survivors, using statistical models to identify patient subgroups most likely to benefit, optimize work reintegration timing, and segment individuals by projected recovery and long-term quality-of-life.
Analysis of an RCT testing the effect of incentives on vaccine uptake
This repository showcases key study designs used in public health research, providing a practical, hands-on learning resource for students and early-career researchers. It covers the full research workflow—from problem definition and study design to statistical analysis and interpretation—using structured examples and synthetic datasets.
Simple random table generator for clinical trials - R/Shiny app
BriDGE: Behavioural research by integrating DAGs and GAMs in Experiments — R package for mechanistic causal analysis of RCT data (causal discovery, GAM-based mediation, bootstrap inference). Companion to Veltri & Banerjee (in press, Behavior Research Methods).
Test (un)confoundedness by comparing an effect from an RCT-like dataset to the same estimand from an observational dataset. Supports IPW/AIPW, bootstrap CIs, a Wald test, and optional transportability weighting (manual or auto-detected via KS/energy tests).
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