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I am working for my thesis on 3 known datasets adult,titanic and compass receidivism and i am trying to generate missing values for different missing rates on attributes(e.g Sex,Race) that contain categorical data.I've read a paper Generating Synthetic Missing Data: A Review by Missing Mechanism but it only describes ways for creating missing data for numerical methods and all the other papers i've read they only talk for numerical data.I've figured out how to create missing data under the MCAR assumption but i find it really difficult to create missing data for MNAR and MAR assumptions .I am really stuck and i dont know what to do.

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You can create a new attribute for example "unknown" and replace the missing values with it as it stated in this article https://medium.com/analytics-vidhya/ways-to-handle-categorical-column-missing-data-its-implementations-15dc4a56893
For the MNAR assumptions, check this documentation I find the explanations pretty good: https://support.sas.com/documentation/cdl/en/statug/66859/HTML/default/viewer.htm#statug_mi_details59.htm

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