Title: | Translation of Logit Regression Coefficients into Percentages |
---|---|
Description: | Translation of logit models coefficients into percentages, following Deauvieau (2010) <doi:10.1177/0759106309352586>. |
Authors: | Nicolas Robette [aut, cre] |
Maintainer: | Nicolas Robette <[email protected]> |
License: | GPL (>= 2) |
Version: | 1.0 |
Built: | 2024-11-25 05:08:53 UTC |
Source: | https://github.com/cran/translate.logit |
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).
data(Music)
data(Music)
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.
'NA' stands for 'not available'
data(Music) str(Music)
data(Music) str(Music)
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)
translate.logit(formula,data,nit=0)
translate.logit(formula,data,nit=0)
formula |
an object of class |
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. |
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.
The function returns a list:
glm |
An object of class |
summary |
The results of |
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 |
Nicolas Robette
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.
## 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)
## 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)