Epidemiology analysis package
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Updated
May 7, 2023 - Python
Epidemiology analysis package
WeightIt: an R package for propensity score weighting
📦 R/haldensify: Highly Adaptive Lasso Conditional Density Estimation
📦 R/medoutcon: Efficient Causal Mediation Analysis with Natural and Interventional Direct/Indirect Effects
Use regression, inverse probability weighting, and matching to close confounding backdoors and find causation in observational data
📦 🎲 R/medshift: Causal Mediation Analysis for Stochastic Interventions
IPW- and CBPS-type propensity score reweighting, with various extensions (Stata package)
Tools for using marginal structural models (MSMs) to answer causal questions in developmental science.
R package for estimating balancing weights using optimization
Targeted maximum likelihood estimation (TMLE) enables the integration of machine learning approaches in comparative effectiveness studies. It is a doubly robust method, making use of both the outcome model and propensity score model to generate an unbiased estimate as long as at least one of the models is correctly specified.
Code for assessing the causal effects of chemotherapy Received Dose Intensity (RDI) on survival outcomes in osteosarcoma patients using a Target Trial Emulation approach.
💬 Talk on "Sensitivity Analysis for Inverse Probability Weighting Estimators via the Percentile Bootstrap" (Q. Zhao et al., 2017), for S. Pimentel's "Observational Study Design and Causal Inference" seminar at Berkeley, Spring 2018
An implementation of g-methods
The R package trajmsm is based on the paper Marginal Structural Models with Latent Class Growth Analysis of Treatment Trajectories: https://doi.org/10.48550/arXiv.2105.12720.
Repository for "The Economic Consequences of UN Peacekeeping Operations: Causal Analysis for Conflict Management and Peace Research"
Inverse probability weighting for non-binary exposures. Simple example in Excel and SAS.
air pollution and mortality/readmission in ADRD population with Medicare data
💬 Talk on causal inference and variable importance with stochastic interventions under two-phase sampling
A questionnaire containing 40+ questions is given to hundreds of people. People are interviewed about their feelings and hobbies with a goal to find the causal relationship between depression and cognitive impairment, where some questions are related to depression, some to cognitive impairment, and others are confounding. In psychological survey…
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