Title: Binning Variables to Use in Logistic Regression
Description: Fast binning of multiple variables using parallel processing. A summary of all the variables binned is generated which provides the information value, entropy, an indicator of whether the variable follows a monotonic trend or not, etc. It supports rebinning of variables to force a monotonic trend as well as manual binning based on pre specified cuts. The cut points of the bins are based on conditional inference trees as implemented in the partykit package. The conditional inference framework is described by Hothorn T, Hornik K, Zeileis A (2006) <doi:10.1198/106186006X133933>.
Imports: partykit, doParallel, data.table, foreach, iterators, parallel

Imports: partykit, doParallel, data.table, foreach, iterators,

Title: Salary Analysis by the Swiss Federal Office for Gender Equality
person(given = "Jonathan", family = "Chassot", email = "logib@ebg.admin.ch",
person(given = "Jeremy", family = "Kolly", email = "logib@ebg.admin.ch",
person(given = "Federal Office for Gender Equality of Switzerland",
email = "ebg@ebg.admin.ch", role = c("cph", "fnd"))
Description: Implementation of the Swiss Confederation's standard analysis model for salary analyses <https://www.ebg.admin.ch/dam/ebg/en/dokumente/lohngleichheit/infos-zu-analysen/standard-analysemodellzurueberpruefungderlohngleichheitzwischenf.pdf.download.pdf/methodological_approachformonitoringcompliancewithwageequalitybe.pdf> in R. The analysis is run at company-level and the model is intended for companies with 50 or more employees (apprentices, trainees/interns and expats are not included in the analysis). Employees with at least 100 employees are required by the Gender Equality Act to conduct an equal pay analysis.
This package allows users to run the equal salary analysis in R, providing additional transparency with respect to the methodology and simple automation possibilities.
Imports: lubridate (>= 1.7.9), readxl (>= 1.3.1)
Federal Office for Gender Equality of Switzerland [cph, fnd]