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ISCA
View on CRAN: Click
here
Download and install ISCA package within the R console
Install from CRAN:
install.packages("ISCA")
Install from Github:
library("remotes")
install_github("cran/ISCA")
Install by package version:
library("remotes")
install_version("ISCA", "0.1.0")
Attach the package and use:
library("ISCA")
Maintained by
Lucas Drouhot
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
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First Published: 2024-10-02
Latest Update: 2024-10-02
Description:
The Inductive Subgroup Comparison Approach ('ISCA') offers a way to compare groups that are internally differentiated and heterogeneous. It starts by identifying the social structure of a reference group against which a minority or another group is to be compared, yielding empirical subgroups to which minority members are then matched based on how similar they are. The modelling of specific outcomes then occurs within specific subgroups in which majority and minority members are matched. 'ISCA' is characterized by its data-driven, probabilistic, and iterative approach and combines fuzzy clustering, Monte Carlo simulation, and regression analysis. ISCA_random_assignments() assigns subjects probabilistically to subgroups. ISCA_clustertable() provides summary statistics of each cluster across iterations. ISCA_modeling() provides Ordinary Least Squares regression results for each cluster across iterations. For further details please see Drouhot (2021) <doi:10.1086/712804>.
How to cite:
Lucas Drouhot (2024). ISCA: Compare Heterogeneous Social Groups. R package version 0.1.0, https://cran.r-project.org/web/packages/ISCA. Accessed 17 Feb. 2025.
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