smallerize

Python module implementing minimization algorithm for clinical trials.

Pure Nim score 15/100 · last commit 2020-01-27 · 1 stars · tests present · no docs generated

Summary

Latest Version Unknown
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Last Commit 2020-01-27
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Last Indexed 2026-08-11 05:08

Installation

nimble install smallerize
choosenim install smallerize
git clone https://gitlab.com/warsquid/smallerize

OS Compatibility

Platform Linux macOS Windows FreeBSD OpenBSD NetBSD Android iOS WASM Embedded
smallerize ✓ ✓ ✓ - - - - - - -

Source

Repository https://gitlab.com/warsquid/smallerize
Homepage https://gitlab.com/warsquid/smallerize
Registry Source gitlab

README

========== smallerize ==========

.. image:: https://img.shields.io/pypi/v/smallerize.svg :target: https://pypi.python.org/pypi/smallerize :alt: pip version

.. image:: https://gitlab.com/warsquid/smallerize/badges/master/pipeline.svg :target: https://gitlab.com/warsquid/smallerize/commits/master :alt: pipeline status

.. image:: https://gitlab.com/warsquid/smallerize/badges/master/coverage.svg :alt: Coverage

.. image:: https://readthedocs.org/projects/smallerize/badge/?version=latest :target: https://smallerize.readthedocs.io/en/latest/?badge=latest :alt: Documentation Status

A Python implementation of minimisation for clinical trials

  • Open source: Mozilla Public License 2.0
  • Documentation: https://smallerize.readthedocs.io.
  • Source: https://gitlab.com/warsquid/smallerize.

Features

  • Implements minimization as described in Pocock + Simon (1975): Sequential treatment assignment with balancing for prognostic factors in the controlled clinical trial
  • Tested using pytest to ensure the results match the original implementation.
  • Pure Python module with no dependencies (pandas is useful when conducting simulations but is optional)
  • Includes all functions described in the article: range, standard deviation, variance, etc.
  • Also implements the biased-coin minimization method described in Han et al. (2009): Randomization by minimization for unbalanced treatment allocation, to allow for unequal allocation ratios.
  • Allows pure random assignment for comparison
  • Simulation module to allow simulating the effects of different assignment schemes.

Example

Comparing minimization to purely random assignment by simulation:

.. image:: https://gitlab.com/warsquid/smallerize/raw/master/examples/ps1975_factor_imbalance_small.png :width: 810 :height: 360 :alt: Simulation results

See the example notebook_ for details of the simulation.

.. _notebook: https://gitlab.com/warsquid/smallerize/blob/master/examples/ps1975_simulations.ipynb

Credits

This package was created with Cookiecutter_ and the audreyr/cookiecutter-pypackage_ project template.

.. Cookiecutter: https://github.com/audreyr/cookiecutter .. audreyr/cookiecutter-pypackage: https://github.com/audreyr/cookiecutter-pypackage