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MMRcaseselection  

Case Classification and Selection Based on Regression Results
View on CRAN: Click here


Download and install MMRcaseselection package within the R console
Install from CRAN:
install.packages("MMRcaseselection")

Install from Github:
library("remotes")
install_github("cran/MMRcaseselection")

Install by package version:
library("remotes")
install_version("MMRcaseselection", "0.2.0")



Attach the package and use:
library("MMRcaseselection")
Maintained by
Ingo Rohlfing
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-03
Latest Update:
Description:
Researchers doing a mixed-methods analysis (nested analysis as developed by Lieberman (2005) ) can use the package for the classification of cases and case selection using results of a linear regression. One can designate cases as typical, deviant, extreme and pathway case and use different case selection strategies for the choice of a case belonging to one of these types.
How to cite:
Ingo Rohlfing (2020). MMRcaseselection: Case Classification and Selection Based on Regression Results. R package version 0.2.0, https://cran.r-project.org/web/packages/MMRcaseselection. Accessed 05 Oct. 2026.
Previous versions and publish date:
0.1.0 (2020-06-03 13:40), (2026-07-09 08:09)
Other packages that cited MMRcaseselection R package
View MMRcaseselection citation profile
Other R packages that MMRcaseselection depends, imports, suggests or enhances
Complete documentation for MMRcaseselection
Functions, R codes and Examples using the MMRcaseselection R package
Some associated functions: extreme_on_x . extreme_on_y . most_deviant . most_overpredicted . most_typical . most_underpredicted . pathway . pathway_xvr . predint . predint_plot . residstd . residstd_plot . 
Some associated R codes: classification.R . deviant.R . extreme.R . globalvariables.R . most_typical.R . pathway.R .  Full MMRcaseselection package functions and examples
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