pyCompare 1.0.0

A Python module to generate `Bland-Altman <https://en.wikipedia.org/wiki/Bland–Altman_plot>`_ plots to compare two measurements.

::
blandAltman(data1, data2, limitOfAgreement=1.96, confidenceInterval=None, confidenceIntervalMethod='exact paired', detrend=None, **kwargs)

Generate a Bland-Altman [#]_ [#]_ plot to compare two sets of measurements of the same value.

`data1` and `data2` should be 1D numpy arrays of equal length containing the paired measurements.

Confidence intervals on the limit of agreement may be calculated using:
- 'exact paired' uses the exact paired method described by Carkeet [#]_
- 'approximate' uses the approximate method described by Bland & Altman

The exact paired method will give more accurate results when the number of paired measurements is low (approx < 100), at the expense of much slower plotting time.

The *detrend* option supports the following options:
- ``None`` do not attempt to detrend data - plots raw values
- 'Linear' attempt to model and remove a multiplicative offset between each assay by linear regression

.. [#] Altman, D. G., and Bland, J. M. “Measurement in Medicine: The Analysis of Method Comparison Studies” Journal of the Royal Statistical Society. Series D (The Statistician), vol. 32, no. 3, 1983, pp. 307–317. `JSTOR <https://www.jstor.org/stable/2987937>`_.
.. [#] Altman, D. G., and Bland, J. M. “Measuring agreement in method comparison studies” Statistical Methods in Medical Research, vol. 8, no. 2, 1999, pp. 135–160. `DOI <https://doi.org/10.1177/096228029900800204>`_.
.. [#] Carkeet, A. "Exact Parametric Confidence Intervals for Bland-Altman Limits of Agreement" Optometry and Vision Science, vol. 92, no 3, 2015, pp. e71–e80 `DOI <https://doi.org/10.1097/OPX.0000000000000513>`_.