smallerize

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A Python implementation of minimisation for clinical trials

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:

Simulation results

See the example notebook for details of the simulation.

Credits

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

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