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A Python package for performing indirect treatment comparisons

Home Page: https://aidancooper.github.io/indcomp/

License: MIT License

Python 2.20% Jupyter Notebook 19.30% R 1.75% HTML 73.54% TeX 3.21%

itc maic stc ml-nmr indirect treatment comparsion matching adjusted multi-level

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indcomp's Issues

`MAIC.compare_populations` method errors when only one variable is provided

Describe the bug
When the MAIC.compare_populations method is run with a single variable, there is an AttributeError

To Reproduce
Steps to reproduce the behaviour:

Configure MAIC to match one variable on one statistic.
Run the compare_populations method
Observe: "AttributeError: 'AxesSubplot' object has no attribute 'flatten'"

Expected behaviour
Populations plot is returned for the single variable/statistic.

Additional context
This can be fixed by dealing with the edge case where only a single variable is provided - the code currently expects 2+.

Add 'min' and 'max' statistics as matching criteria

Describe the solution you'd like
As a user, I want to be able to specify minimum and maximum permitted values for selected characteristics in my adjusted population.

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