stargazer R: Display mulitple regression with different data next to each other
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I´m wirting on my bachelor´s thesis and have a problem with the stragazer function in R.
Basic question: What drives unemployment? Therefore I ran a logit-regression to estimate what factors raise the probability to get unemployed. I have 7 different data frames of 7 different years, so I run 7 different logit regressions with the same dependent (and independent) variables. (In this case its only the effect of age i´m interested in.
logit17 <- glm(formula = data17$AL ~ data17$age,
family = "binomial", data = data17)
logit16 <- glm(formula = dataP_16$AL ~ dataP_16$age,
family = "binomial", data = data16)
So far so easy. The problem I am facing now:
When running the regressions through stargazer, the out output looks like the following:
Apparently stargazer recognizes age as two different variables (which they kinda are, because it´s a different data set). In addtion, when I insert more variables and the regressions of the other years the table gets extremly long.
My question: Is there any function to avoid these huge tables? I guess I somehow need to tell stargazer that it should treat age and the other variable as one.
Thanks
r regression stargazer
add a comment |
up vote
0
down vote
favorite
I´m wirting on my bachelor´s thesis and have a problem with the stragazer function in R.
Basic question: What drives unemployment? Therefore I ran a logit-regression to estimate what factors raise the probability to get unemployed. I have 7 different data frames of 7 different years, so I run 7 different logit regressions with the same dependent (and independent) variables. (In this case its only the effect of age i´m interested in.
logit17 <- glm(formula = data17$AL ~ data17$age,
family = "binomial", data = data17)
logit16 <- glm(formula = dataP_16$AL ~ dataP_16$age,
family = "binomial", data = data16)
So far so easy. The problem I am facing now:
When running the regressions through stargazer, the out output looks like the following:
Apparently stargazer recognizes age as two different variables (which they kinda are, because it´s a different data set). In addtion, when I insert more variables and the regressions of the other years the table gets extremly long.
My question: Is there any function to avoid these huge tables? I guess I somehow need to tell stargazer that it should treat age and the other variable as one.
Thanks
r regression stargazer
The modeling function code should be:glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to theglm
function with thedata
argument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I´m wirting on my bachelor´s thesis and have a problem with the stragazer function in R.
Basic question: What drives unemployment? Therefore I ran a logit-regression to estimate what factors raise the probability to get unemployed. I have 7 different data frames of 7 different years, so I run 7 different logit regressions with the same dependent (and independent) variables. (In this case its only the effect of age i´m interested in.
logit17 <- glm(formula = data17$AL ~ data17$age,
family = "binomial", data = data17)
logit16 <- glm(formula = dataP_16$AL ~ dataP_16$age,
family = "binomial", data = data16)
So far so easy. The problem I am facing now:
When running the regressions through stargazer, the out output looks like the following:
Apparently stargazer recognizes age as two different variables (which they kinda are, because it´s a different data set). In addtion, when I insert more variables and the regressions of the other years the table gets extremly long.
My question: Is there any function to avoid these huge tables? I guess I somehow need to tell stargazer that it should treat age and the other variable as one.
Thanks
r regression stargazer
I´m wirting on my bachelor´s thesis and have a problem with the stragazer function in R.
Basic question: What drives unemployment? Therefore I ran a logit-regression to estimate what factors raise the probability to get unemployed. I have 7 different data frames of 7 different years, so I run 7 different logit regressions with the same dependent (and independent) variables. (In this case its only the effect of age i´m interested in.
logit17 <- glm(formula = data17$AL ~ data17$age,
family = "binomial", data = data17)
logit16 <- glm(formula = dataP_16$AL ~ dataP_16$age,
family = "binomial", data = data16)
So far so easy. The problem I am facing now:
When running the regressions through stargazer, the out output looks like the following:
Apparently stargazer recognizes age as two different variables (which they kinda are, because it´s a different data set). In addtion, when I insert more variables and the regressions of the other years the table gets extremly long.
My question: Is there any function to avoid these huge tables? I guess I somehow need to tell stargazer that it should treat age and the other variable as one.
Thanks
r regression stargazer
r regression stargazer
edited Nov 22 at 16:53
eipi10
57.9k15101154
57.9k15101154
asked Nov 22 at 15:32
rstarter
1
1
The modeling function code should be:glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to theglm
function with thedata
argument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37
add a comment |
The modeling function code should be:glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to theglm
function with thedata
argument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37
The modeling function code should be:
glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to the glm
function with the data
argument, and it can have undesirable effects, as explained here.– eipi10
Nov 22 at 17:00
The modeling function code should be:
glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to the glm
function with the data
argument, and it can have undesirable effects, as explained here.– eipi10
Nov 22 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37
add a comment |
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The modeling function code should be:
glm(formula = AL ~ age, family = "binomial", data = data17)
. In other words, don't restate the data frame name in the formula. It's not necessary to do so, because you passed the data frame to theglm
function with thedata
argument, and it can have undesirable effects, as explained here.– eipi10
Nov 22 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 at 13:37