Bland-Altman plots for Python
Project description
pyCompare ![](https://pypi-camo.freetls.fastly.net/748600441cd1d1e5cbfee02fc0c8cb8a2b382b5b/68747470733a2f2f6769746875622e636f6d2f6a616b65746d702f7079436f6d706172652f7261772f6d61737465722f646f63732f5f7374617469632f7079436f6d706172652e706e67)
A Python module for generating Bland-Altman plots to compare two sets of measurements.
You can try out the code using Binder.
Installation
To install via pip, run:
pip install pyCompare
Installation with pip allows the usage of the uninstall command:
pip uninstall pyCompare
Documentation
blandAltman( )
blandAltman(data1, data2,
limitOfAgreement=1.96,
confidenceInterval=95,
confidenceIntervalMethod='approximate',
detrend=None,
percentage=False,
**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.
If not None
plot confidence interval over the x% range with confidenceInterval=x
Confidence intervals on the mean difference and 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 confidence intervals on the limits of agreement when the number of paired measurements is low (approx < 100), at the expense of much slower plotting time.
The detrend parameter 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
- 'ODR' attempt to model and remove a multiplicative offset between each assay by orthogonal distance regression
'ODR' is the recommended method if you do not use None
.
When True
, the percentage
option plots the difference between methods as a percentage, instead of in the units the methods were measured in.
Plots are displayed using the current matplotlib backend by default, or may be saved with the savePath=
argument.
When saving, png format graphics are saved by default:
blandAltman(data1, data2,
savePath='SavedFigure.png')
The save format type can be chosen from those known by matplotlib with the figureFormat=
argument:
blandAltman(data1, data2,
savePath='SavedFigure.svg',
figureFormat='svg)
References
To cite pyCompare
, use the Zendo DOI: 10.5281/zenodo.1238915.
- 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.
- 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.
- 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.
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