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  "Maintainer": "Lucas Drouhot <l.g.m.drouhot@uu.nl>",
  "License": "GPL (>= 3)",
  "Title": "Compare Heterogeneous Social Groups",
  "Description": "The Inductive Subgroup Comparison Approach ('ISCA') offers\na way to compare groups that are internally differentiated and\nheterogeneous. It starts by identifying the social structure of\na reference group against which a minority or another group is\nto be compared, yielding empirical subgroups to which minority\nmembers are then matched based on how similar they are. The\nmodelling of specific outcomes then occurs within specific\nsubgroups in which majority and minority members are matched.\n'ISCA' is characterized by its data-driven, probabilistic, and\niterative approach and combines fuzzy clustering, Monte Carlo\nsimulation, and regression analysis. ISCA_random_assignments()\nassigns subjects probabilistically to subgroups.\nISCA_clustertable() provides summary statistics of each cluster\nacross iterations. ISCA_modeling() provides Ordinary Least\nSquares regression results for each cluster across iterations.\nFor further details please see Drouhot (2021)\n<doi:10.1086/712804>.",
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