haghish/mlim
mlim: single and multiple imputation with automated machine learning
This tool helps researchers and analysts handle missing information in their datasets. It takes your raw data, even with gaps for continuous, binary, multinomial, or ordinal variables, and fills them in with highly accurate and fair estimates. The end result is a complete dataset ready for analysis, used by anyone working with real-world data, especially in social sciences.
Use this if you need to fill in missing values in your dataset accurately and fairly, especially when dealing with complex data that might have class imbalance or variable interactions.
Not ideal if you prefer traditional statistical imputation methods without machine learning, or if you need to strictly adhere to specific distributional assumptions.
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Language
R
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Last pushed
Feb 22, 2026
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