experimental-design

For running psychology and neuroscience experiments

YACS -- Yet Another Configuration System

A Python-based toolbox of various methods in uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

A JavaScript port of Facebook's PlanOut Experimentation Framework

Power analysis is essential to optimize the design of RNA-seq experiments and to assess and compare the power to detect differentially expressed genes. PowsimR is a flexible tool to simulate and evaluate differential expression from bulk and especially single-cell RNA-seq data making it suitable for a priori and posterior power analyses.

Covariate Balance Tables and Plots - An R package for assessing covariate balance

Olympus: a benchmarking framework for noisy optimization and experiment planning

This Python library implements Trimmed Match for analyzing randomized paired geo experiments and also implements Trimmed Match Design for designing randomized paired geo experiments.

ParamHelpers Next Generation

A minimalist framework for rapid server side applications prototyping in C++ with dependency injection support.

Design of Experiments in Julia

Bayesian Information Gap Decision Theory

An R Package and Shiny App for generating matched stimuli for Psychology experiments.

効果検証入門のコードをPythonで実装しました。

💫 Computer-aided DNA assembly validation and identification from restriction digests.

Experimental design and Bayesian optimization library in Python/PyTorch

TriScale software

AB Testing

Causal Inference Using Quasi-Experimental Methods

This package underwent major revisions and is now available as powsimR!

BonVision is an open-source closed-loop visual environment generator developed by the Saleem Lab and Solomon Lab at the UCL Institute of Behavioural Neuroscience in collaboration with NeuroGEARS.

Golem: an algorithm for robust experiment and process optimization

Experimental Design & Recommendations Project of Udacity Data Scientist Nanodegree

A Python Package for intuitive design of experiments with user-friendly analysis of results. The aim is for this package to rival the DOE capabilities of commercial software such as JMP. Currently designs and analysis will be more geared towards investigations following the Response Surface Methodology.

Template structure for behavioural tasks.

Experiments in Virtual Environments

Tools for experimental design and multi-objective optimization.

A statistical simulator for rational scRNA-seq experimental design

Work in progress parser, interpreter, and API for the PlanOut experimentation framework.