Select a random list of test group/individuals and provides the best matching group/individuals for a control based on a dataframe of metrics for the subjects. Or you can generate control groups/individuals for a list of pre-selected test groups. For the numeric functions, Euclidian distance is used for the pairing. For datasets with mixed variables, Gower's distance matrix derived with the cluster::daisy() function is used for the pairing. Categorical variables are know account as of version 1.1.0.
|License||MIT + file LICENSE|
|Package repository||View on GitHub|
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