Treatment-effects estimation by blop-matching in Stata

To Impute or not to Impute? Missing Data in Treatment Effect Estimation

In this theoretical work we provide an unrestricted linear model for identifying treatment effects with time-varying qualification with panel data and repeated cross-sections. This model enables fixed and random effects estimation of treatment effects; the latter has not been considered before. In addition we identify new scenarios and respectiv…

Review: Data-driven methodology for detecting treatment effect heterogeneity

📹 Análise de dados sobre psicoeducação em vídeo do projeto TelePsi.

Github for the final project in Econometrics. Replication of Cameron, Gelbach and Miller (2008) and extension to "skewed" treatment variable.

Quantifying the Persistence of Misinformation: A Case Study in R

Repository of causal inference models, with a shared syntax for users to swap between models. This repository also allows users to diagnose their causal estimates absent any ground truth measures.

Comparison of treatment effect in Randomized Control Trial (RCT) and Propensity Score Matching methods, conducted on Large-Scale Dataset by 'Criteo'.

Accounting for hidden confounders in estimates of dose-response curves from observational data.

Stata command abseff (immediate calculation of absolute effects from relative treatment estimates)

Multiple Responses Subgroup Identification

KRAS-mutant pancreatic ductal adenocarcinoma (PDAC) is highly immunosuppressive and resistant to targeted therapies, immune checkpoint blockade and engineered T cells. In this study, we performed a systematic high throughput combinatorial drug screen and identified a synergistic interaction between the MEK inhibitor trametinib and the multi- kin…

This is a demonstration of how we can implement Hirano-Imbens (2004) model for estimating Average Dose Response Function under Normally distributed continuous treatment.

R code (Rmd and Rnw) of the analysis on treatment effect of income on religiousness (Busser 2015)

Find sub groups (segments) with heterogeneous treatment effect in Randomised Controlled Trial data.

Estimating the Effect of Persuasion in Stata

Estimating the Effect of Persuasion in Stata

A modified uplift modeling technique to convert "treatment nonresponders" to "responders" is proposed through multifaceted interventions in market campaigns.

Automatic Stopping for Batch-mode Experimentation