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        "author": "Marius Mather",
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            "License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)",
            "Natural Language :: English",
            "Programming Language :: Python :: 3.6",
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        "description": "==========\nsmallerize\n==========\n\n\n.. image:: https://img.shields.io/pypi/v/smallerize.svg\n        :target: https://pypi.python.org/pypi/smallerize\n        :alt: pip version\n\n.. image:: https://gitlab.com/warsquid/smallerize/badges/master/pipeline.svg\n        :target: https://gitlab.com/warsquid/smallerize/commits/master\n        :alt: pipeline status\n\n.. image:: https://gitlab.com/warsquid/smallerize/badges/master/coverage.svg\n        :alt: Coverage\n\n.. image:: https://readthedocs.org/projects/smallerize/badge/?version=latest\n        :target: https://smallerize.readthedocs.io/en/latest/?badge=latest\n        :alt: Documentation Status\n\n\n\n\nA Python implementation of minimisation for clinical trials\n\n\n* Open source: Mozilla Public License 2.0\n* Documentation: https://smallerize.readthedocs.io.\n* Source: https://gitlab.com/warsquid/smallerize.\n\n\nFeatures\n--------\n\n* Implements minimization as described in Pocock + Simon (1975): *Sequential\n  treatment assignment with balancing for prognostic factors in the\n  controlled clinical trial*\n* Tested using ``pytest`` to ensure the results match the original\n  implementation.\n* Pure Python module with no dependencies (``pandas`` is useful when conducting\n  simulations but is optional)\n* Includes all functions described in the article: range, standard deviation,\n  variance, etc.\n* Also implements the biased-coin minimization method described in Han et al. (2009):\n  *Randomization by minimization for unbalanced treatment allocation*, to\n  allow for unequal allocation ratios.\n* Allows pure random assignment for comparison\n* Simulation module to allow simulating the effects of different assignment\n  schemes.\n\nExample\n-------\n\nComparing minimization to purely random assignment by simulation:\n\n.. image:: https://gitlab.com/warsquid/smallerize/raw/master/examples/ps1975_factor_imbalance.png\n        :width: 1350\n        :height: 600\n        :scale: 50%\n        :alt: Simulation results\n\nSee the example `notebook`_  for details of the simulation.\n\n.. _notebook: https://gitlab.com/warsquid/smallerize/blob/master/examples/ps1975_simulations.ipynb\n\nCredits\n-------\n\nThis package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.\n\n.. _Cookiecutter: https://github.com/audreyr/cookiecutter\n.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage\n\n\n=======\nHistory\n=======\n\n0.5.0 (2019-05-08)\n-------------------\n\n* Improved performance with large numbers of factors/factor levels by\n  making the count table sparse.\n\n0.4.0 (2019-02-02)\n------------------\n\n* Switched to Mozilla Public License.\n\n0.3.0 (2019-01-02)\n------------------\n\n* Make it easier to check the valid total imbalance and\n  probability methods.\n\n0.2.0 (2018-10-22)\n------------------\n\n* Add the biased coin minimization method to allow\n  for unequal treatment allocations.\n\n0.1.0 (2018-10-07)\n------------------\n\n* First release on PyPI.\n\n\n",
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