shuyang-stat Goto Github PK

amw_for_submit

causalml

Uplift modeling and causal inference with machine learning algorithms

combine-rct-rwd-review

R notebooks associated with the review article: "Causal inference methods for combining randomized controlled trials and observational studies: a review"

conttimecausal

Continuous Time Causal Models for Time-varying Treatments

easy-blog-setup

elasticintegrative

Elastic integrative analysis for heterogenous treatment effect combining a randomized clinical trial (RCT) and a real-world evidence (RWE) study

elasticintegrativeanalysis

fpca

to implement FPCA with informative observation times

genrct

Generalizing the average treatment effect (ATE) from the trial using observational studies (OS)

integrativeci

Integrative analyses of the average treatment effect combining big main data and smaller validation data

integrativefpm

integrativehtecf

Integrative analysis of the HTE and confounding functions combining RCT and RWE with unmeasured confounders

low-rank-tensor-block-hazard-model

The repository implements the codes for causal customer churn analysis with low-rank tensor block hazard model

missingdata_dl

multilevelmatching

Propensity score Matching and Subclassification with 3 or more Treatments

myhrcpp

An R package for Ming-Yueh's work

pace

Implements multiply robust estimators of average causal effects within principal strata (pace)

peerloss

Learning with Noisy Labels by adopting a peer prediction loss function.

ser2022-workshop

Materials for two half-day workshops on Targeted Learning with the tlverse at the 2022 Society for Epidemiologic Research Meeting

spqr

Semi-Parametric Quantile Regression

tigramite

Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at

transfer-learning-survival-itr