Type: Package
Title: Translation of Logit Regression Coefficients into Percentages
Version: 1.0
Imports: nleqslv, nnet
Description: Translation of logit models coefficients into percentages, following Deauvieau (2010) <doi:10.1177/0759106309352586>.
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2023-02-22 18:01:46 UTC; nicolas
Author: Nicolas Robette [aut, cre]
Maintainer: Nicolas Robette <nicolas.robette@uvsq.fr>
Repository: CRAN
Date/Publication: 2023-02-23 09:50:04 UTC

Music (data)

Description

The data concerns tastes for music of a set of 500 individuals. It contains 5 variables of likes for music genres (french pop, rap, rock, jazz and classical), 2 about music listening and 2 additional variables (gender and age).

Usage

data(Music)

Format

A data frame with 500 observations and the following 7 variables:

FrenchPop

is a factor with levels No, Yes, NA

Rap

is a factor with levels No, Yes, NA

Rock

is a factor with levels No, Yes, NA

Jazz

is a factor with levels No, Yes, NA

Classical

is a factor with levels No, Yes, NA

Gender

is a factor with levels Men, Women

Age

is a factor with levels 15-24, 25-49, 50+

OnlyMus

is a factor with levels Daily, Often, Rare, Never, indicating how often one only listens to music.

Daily

is a factor with levels No, Yes indicating if one listens to music every day.

Details

'NA' stands for 'not available'

Examples

data(Music)
str(Music)

Translates logit regression coefficients into percentages

Description

Performs a logit regression and then computes the effects of covariates expressed in percentages (through two methods: 'pure' effects and 'experimental' effects; see Deauvieau, 2010)

Usage

translate.logit(formula,data,nit=0)

Arguments

formula

an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted.

data

a data frame containing the variables in the model. Every variables have to be factors.

nit

number of bootstrap iterations for confidence interval computation. Default is 0, i.e. no confidence interval is computed.

Details

This function works with binomial as well as multinomial regression models. If the dependent variable has two factors, glm is used ; if it has more than two factors multinom function (from nnet package) is used.

The function expresses the regression coefficients as percentages through three distinct methods: raw percentages, 'pure effects' percentages and 'experimental effects' percentages (see Deauvieau, 2010).

Bootstrap confidence interval are available only for binomial regressions.

Value

The function returns a list:

glm

An object of class glm or nnet (depending on the number of factors of the dependent variable)

summary

The results of summary function applied to reg element

percents

A matrix or a list of matrices (depending on the number of factors of the dependent variable) with regression coefficients expressed as percentages

boot.ci

A matrix or a list of matrices (depending on the number of factors of the dependent variable) with confidence intervals computed with bootstrap

Author(s)

Nicolas Robette

References

Deauvieau, J. (2010), 'Comment traduire sous forme de probabilites les resultats d'une modelisation logit ?', Bulletin of Sociological Methodology / Bulletin de Methodologie Sociologique 105(1), 5-23.

Deauvieau, J. (2011), 'Est-il possible et souhaitable traduire sous forme de probabilites un coefficient logit ? Reponse aux remarques formulees par Marion Selz a propos de mon article paru dans le BMS en 2010', Bulletin of Sociological Methodology / Bulletin de Methodologie Sociologique 112(1), 32-42.

Deauvieau, J. (2019), 'Comparer les resultats d’un modele logit dichotomique ou polytomique entre plusieurs groupes a partir des probabilites estimees', Bulletin of Sociological Methodology / Bulletin de Methodologie Sociologique 142(1), 7-31.

See Also

glm, multinom

Examples

  ## An example for binomial logit regression
  data(Music)
  translate.logit(Daily ~ Gender + Age, Music)

  ## An example for multinomial logit regression
  translate.logit(OnlyMus ~ Gender + Age, Music)