limit output of control categorical variable R
I have a categorical variable with more than 15 categories. When I use it in regression:
Reg <- lm(DV ~ IV1 + IV2 + Category, data = mydata)
It creates a dummy for each category which is perfectly what I want, but I don't want to see each dummy in my output when I use:
summary(Reg)
Is there a way to just see 'Category' as one variable in output? I have another categorical variable with 135 categories...
r lm categorical-data
asked Nov 13 '18 at 3:04
naimnaim2001
112
add a comment |
I have a categorical variable with more than 15 categories. When I use it in regression:
Reg <- lm(DV ~ IV1 + IV2 + Category, data = mydata)
It creates a dummy for each category which is perfectly what I want, but I don't want to see each dummy in my output when I use:
summary(Reg)
Is there a way to just see 'Category' as one variable in output? I have another categorical variable with 135 categories...
r lm categorical-data
asked Nov 13 '18 at 3:04
naimnaim2001
112
add a comment |
I have a categorical variable with more than 15 categories. When I use it in regression:
Reg <- lm(DV ~ IV1 + IV2 + Category, data = mydata)
It creates a dummy for each category which is perfectly what I want, but I don't want to see each dummy in my output when I use:
summary(Reg)
Is there a way to just see 'Category' as one variable in output? I have another categorical variable with 135 categories...
r lm categorical-data
asked Nov 13 '18 at 3:04
naimnaim2001
112
I have a categorical variable with more than 15 categories. When I use it in regression:
Reg <- lm(DV ~ IV1 + IV2 + Category, data = mydata)
It creates a dummy for each category which is perfectly what I want, but I don't want to see each dummy in my output when I use:
summary(Reg)
Is there a way to just see 'Category' as one variable in output? I have another categorical variable with 135 categories...
r lm categorical-data
r lm categorical-data
asked Nov 13 '18 at 3:04
naimnaim2001
112
asked Nov 13 '18 at 3:04
naimnaim2001
112
asked Nov 13 '18 at 3:04
naimnaim2001
112
asked Nov 13 '18 at 3:04
naimnaim2001
112
asked Nov 13 '18 at 3:04
naimnaim2001
112
112
add a comment |
add a comment |
1 Answer
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You could do something like this.
I've used the iris data to fit a linear model:
lm_mod<-lm(Petal.Length~Sepal.Length+Species,data=iris)
Then you can choose a specific variable as follows:
summary(lm_mod$model$Petal.Length)
EDIT: Do you really need to call summary?
answered Nov 13 '18 at 3:12
NelsonGon
817217
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
add a comment |
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1 Answer
1
active
oldest
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1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
You could do something like this.
I've used the iris data to fit a linear model:
lm_mod<-lm(Petal.Length~Sepal.Length+Species,data=iris)
Then you can choose a specific variable as follows:
summary(lm_mod$model$Petal.Length)
EDIT: Do you really need to call summary?
answered Nov 13 '18 at 3:12
NelsonGon
817217
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
add a comment |
You could do something like this.
I've used the iris data to fit a linear model:
lm_mod<-lm(Petal.Length~Sepal.Length+Species,data=iris)
Then you can choose a specific variable as follows:
summary(lm_mod$model$Petal.Length)
EDIT: Do you really need to call summary?
answered Nov 13 '18 at 3:12
NelsonGon
817217
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
add a comment |
You could do something like this.
I've used the iris data to fit a linear model:
lm_mod<-lm(Petal.Length~Sepal.Length+Species,data=iris)
Then you can choose a specific variable as follows:
summary(lm_mod$model$Petal.Length)
EDIT: Do you really need to call summary?
answered Nov 13 '18 at 3:12
NelsonGon
817217
You could do something like this.
I've used the iris data to fit a linear model:
lm_mod<-lm(Petal.Length~Sepal.Length+Species,data=iris)
Then you can choose a specific variable as follows:
summary(lm_mod$model$Petal.Length)
EDIT: Do you really need to call summary?
answered Nov 13 '18 at 3:12
NelsonGon
817217
answered Nov 13 '18 at 3:12
NelsonGon
817217
answered Nov 13 '18 at 3:12
NelsonGon
817217
answered Nov 13 '18 at 3:12
NelsonGon
817217
817217
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
add a comment |
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
I use 'stargazer' package to create a table of regression results. What happens is I get 15 rows for this categorical variable which is very annoying...
– naimnaim2001
Nov 13 '18 at 3:58
add a comment |
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