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

A collection of bias correction techniques written in Python - for climate sciences.

Bias correction command-line tool for climatic research written in C++

This module includes Item Statistics, Model fit, Differential Item Functioning, Wright Map, Expected Scores Curve,and Item Characteristic Curve for DIF using MML estimation of the Rasch measurement model. Furthermore you can analyze DIF, Distractor analysis and Many facet Rasch model.

lightweight R package around covariate adjustment for binary outcomes focusing on marginal estimands

pydisagg is a Python package for disaggregating estimated count observations across groups under generalized proportionality assumptions.

Uncertainty or Standard Error of Mean propagation using Delta and Monte Carlo methods

Compares several ways for calculating confidence interval (CI) of the relative difference of two sample means

Тыкаюсь в темах интенсива A/B-week от ШАДа

Sample-Size Calculations for A/B Testing using Delta method

Research compendium for the manuscript Pesigan, I. J. A., Russell, M. A., & Chow, S.-M. (2025). Inferences and Effect Sizes for Direct, Indirect, and Total Effects in Continuous-Time Mediation Models. Psychological Methods.

cTMed: Continuous-Time Mediation (Pesigan, Russell, & Chow, 2025: https://doi.org/10.1037/met0000779).

Educational projects on online experiments

Performmance/execution time test of the bias correction tool BiasAdjustCXX v1.8 in comparison to python-cmethods v0.6.1 and xclim v0.40.0.

Illustrate the delta-method