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2.3.2

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* Minor bug-fix: No need to raise error when using alternative correction methods, since we return None CIs and print out warning instead

2.3.1

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* Added even more multiple correction strategies

2.3.0

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* Added additional multiple correction methods (Holm, Hommel, Simes-Hochberg) for one sided tests.
* Added verbose mode to summary and difference methods that returns all intermediate columns that are used in the computations

2.2.0

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* Changed how sequential tests are done. Now, instead of passing a single (number) final_expected_sample_size, you pass a column name final_expected_sample_size. This is to ensure that groupby works as expected, i.e. different groups can have different expected sample sizes.

2.1.4

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* Added support for NaNs in NIMs

2.1.3

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* Added option to pass non_inferiority_margins=True which then uses NIMs in source data_frame, rather than passing in dict of tuples with NIMs

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