cuped

A Python package for the statistical analysis of A/B tests

因果推理&AB实验相关论文小书库

Causalis - State-of-the-art robust causal inference for experiments and observational data in python

Theory and implementatuon of various A/B experiments

AB testing, stattests, poisson bootstrap, cuped, linearization

Calibration-driven A/B testing toolkit: SRM, CUPED/CUPAC, delta-method ratio metrics, sequential and Bayesian methods, each validated by tests.

Monte Carlo audit of CUPED variance reduction and post-treatment bad controls

A/B testing statistics, design, increasing sensitivity, multiple experiments comparison, traffic splitting and full A/B testing pipeline in Python

896 tests / 42 scripts validating Zetyra calculators (GSD, CUPED, Bayesian, SSR incl. Single-Arm, RAR, Master Protocol). Replicates 8 published trials (Salk, DAPA-HF, PACIFIC, MONALEESA-7, I-SPY 2, STAMPEDE, REMAP-CAP, NCT03377023) + Leyrat 2024.

Синтетические A/B-эксперименты: CUPED, взвешенные оценки, bias и покрытие интервалов.

A/B testing engine: frequentist + Bayesian + CUPED variance reduction + peeking-safe sequential testing

A/B testing engine with always-valid sequential inference (mSPRT) — peek continuously without inflating false positives. CUPED variance reduction, SRM detection, guardrails. FastAPI + React.

Тыкаюсь в темах интенсива A/B-week от ШАДа

End-to-end A/B test analysis on a synthetic streaming-service experiment. Demonstrates experiment design, frequentist & Bayesian inference, sensitivity analysis, and stakeholder communication.

A Python package for the full A/B test lifecycle, from power analysis to sequential monitoring and variance reduction

End-to-end A/B experimentation toolkit: experiment readouts, MDE & power calculations, CUPED variance reduction, and decision-focused reporting in a Big Tech economist style.

An end-to-end A/B testing program review: 6 experiments, 2 ships, and the decision-quality framework behind them

RetailLab: should a retailer keep sending its marketing e-mail? Prices a 64k-customer randomized experiment at sector margins into Ship / Don't Ship / Keep Testing / Don't Trust.

A/B testing framework with power analysis, SRM diagnostics, CUPED variance reduction, and BH-corrected segment analysis

A/B test analysis toolkit: power analysis, CUPED variance reduction, SRM detection, guardrail metrics