ehrapy.preprocessing.mcar_test#
- ehrapy.preprocessing.mcar_test(adata, method='little', *, layer=None)[source]#
Statistical hypothesis test for Missing Completely At Random (MCAR).
The null hypothesis of the Little’s test is that data is Missing Completely At Random (MCAR).
We advise to use Little’s MCAR test carefully. Rejecting the null hypothesis may not always mean that data is not MCAR, nor is accepting the null hypothesis a guarantee that data is MCAR. See Schouten, R. M., & Vink, G. (2021). The Dance of the Mechanisms: How Observed Information Influences the Validity of Missingness Assumptions. Sociological Methods & Research, 50(3), 1243-1258. https://doi.org/10.1177/0049124118799376 for a thorough discussion of missingness mechanisms.
- Parameters:
- Return type:
- Returns:
A single p-value if the Little’s test was applied or a Pandas DataFrame of the p-value of t-tests for each pair of features.