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Name: Laura B. Balzer
Type: User
Name: Laura B. Balzer
Type: User
Code for "Adaptive Selection of the Optimal Strategy to Improve Precision and Power in Randomized Trials"
Sample R code and simulations to illustrate estimation and inference for the PATE and SATE with the unadjusted estimator, MLE with a priori-specified adjustment set, TMLE with adaptive pre-specification for initial estimation of outcome regression, and C-TMLE including collaborative estimation of the known exposure mechanism.
Modeling COVID-19 epidemic
R code for the commentary "Demystifying Statistical Inference When Using Machine Learning in Causal Research" in AJE
R code to evaluate the UNAIDS 90/90/90 Cascade Coverage in the SEARCH Study - Code by Laura Balzer & Joshua Schwab
R code corresponding to "Far from MCAR: obtaining population-level estimates of HIV viral suppression"
R code to generate simulated data and implement the hierarchical TMLEs described in "A new approach to hierarchical data analysis: Targeted maximum likelihood estimation for the causal effect of a cluster-level exposure", Balzer et al. SMMR 2018.
Introduction to Double Robust Estimation for Causal Inference
Code for simulation study conducted in "Machine Learning in Causal Inference: How do I love thee? Let me count the ways."
R Code to implement simulations in the Invited Commentary: 'All generalizations are dangerous, even this one.' - Dumas # Written by Laura Balzer for Epidemiology 2017
R code for evaluating adult HIV incidence, health, & implementation outcomes for the first phase of the SEARCH Study (https://www.searchendaids.com/). Full statistical analysis plan available at https://arxiv.org/abs/1808.03231
Simulated data to illustrate bias due to confounding
learning how GitHub works
Sample R code and Simulations to illustrate estimation and inference for the sample average treatment effect (SATE) in trials with and without pair-matching.
Analyze randomized trials with TMLE
A declarative, efficient, and flexible JavaScript library for building user interfaces.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.