smallerize 0.3.0

A Python implementation of minimisation for clinical trials

smallerize

A Python implementation of minimisation for clinical trials

• Free software: GNU General Public License v3

• 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

• 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:

Credits

This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

History

0.3.0 (2019-01-02)

• Make it easier to check the valid total imbalance and probability methods.

0.2.0 (2018-10-22)

• Add the biased coin minimization method to allow for unequal treatment allocations.

0.1.0 (2018-10-07)

• First release on PyPI.