CODEWITHSUNDEEP
rplot
user3768644
user3768644

Reputation: 35

coefplot in R with parts of independent variables

I would get a coefplot only with part of independent variables. My regression equation is a fixed effects regression as follows:

aa1 <-glm(Eighty_Twenty ~ Market_Share_H+Market_Share_L+Purchase_Frequency_H+Purchase_Frequency_L+factor(product_group))
coefplot(aa1)

However, I do NOT want to plot coefficients of factor(product_group) variables since there are product groups. Instead, I would get a coefplot with only the coefficients of other variables. How can I do this?

Upvotes: 0

Views: 3008

Answers (1)

user20650
user20650

Reputation: 25854

From the help pages (see ?coefplot.default) you can select what predictors or coefficients that you want in your plot.

# some example data
df <- data.frame(Eighty_Twenty = rbinom(100,1,0.5),
                 Market_Share_H = runif(100),
                 Market_Share_L = runif(100),
                 Purchase_Frequency_H = rpois(100, 40),
                 Purchase_Frequency_L = rpois(100, 40),
                 product_group = sample(letters[1:3], 100, TRUE))

# model
aa1 <- glm(Eighty_Twenty ~ Market_Share_H+Market_Share_L +
                           Purchase_Frequency_H + Purchase_Frequency_L + 
                           factor(product_group), df, family="binomial")


library(coefplot)

# coefficient plot with the intercept
coefplot(aa1, coefficients=c("(Intercept)","Market_Share_H","Market_Share_L",  
                              "Purchase_Frequency_H","Purchase_Frequency_L"))

# coefficient plot specifying predictors (no intercept)
coefplot(aa1, predictors=c("Market_Share_H","Market_Share_L"  ,      
                             "Purchase_Frequency_H","Purchase_Frequency_L"))

Upvotes: 1

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