observational-study

WeightIt: an R package for propensity score weighting

Variable importance through targeted causal inference, with Alan Hubbard

The Ontology for Nutritional Studies (ONS) has been developed as part of the ENPADASI European project (http://www.enpadasi.eu/) with the aim to define a common language and building ontologies for nutritional studies.

R package for estimating balancing weights using optimization

IPW- and CBPS-type propensity score reweighting, with various extensions (Stata package)

Prioritize variables in observational study design through the joint variable importance plot; shiny app: https://ldliao.shinyapps.io/jointVIP/

Targeted Maximum Likelihood Estimation for Hierarchical Data

An application for creating, validating, reusing and extending sets of clinical codes.

Evaluating the association between blood group and COVID-19

Implementation for the paper "Hidden yet quantifiable: A lower bound for confounding strength using randomized trials"

Implementation for the paper "Doubly robust identification of treatment effects from multiple environments"

Code for an analysis of the association of lipid regulating agents (e.g. statins) with incidence of dementia outcomes

[Experimental] Federated Partial Identification for Causal Inference with OMOP CDM

Repository for course work done in CIS 443: User Interfaces.

End-to-end causal inference study estimating the effect of smoking cessation on substantial weight gain using propensity methods, DoWhy, and doubly robust EconML estimators.

A prospective registry assessing hepatic enzyme derangements and inpatient outcomes in hospitalized COVID-19 patients; features GCP and 21 CFR Part 11-compliant eCRF design, data dictionary, and validation workflows.

Propensity scores in complex surveys

Casual relationship between health insurance coverage and BMI.

This repository contains code for curating data and testing hypotheses relating to the College-to-Work Transition study.

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