stargazer R: Display mulitple regression with different data next to each other
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
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
1
add a comment |
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
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
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 theglmfunction with thedataargument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 '18 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 at 13:37
add a comment |
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
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
1
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 '18 at 16:53
eipi10
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
1
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
1
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
edited Nov 22 '18 at 16:53
eipi10
59.6k16108161
59.6k16108161
asked Nov 22 '18 at 15:32
rstarterrstarter
1
asked Nov 22 '18 at 15:32
rstarterrstarter
1
asked Nov 22 '18 at 15:32
rstarterrstarter
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 theglmfunction with thedataargument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 '18 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 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 theglmfunction with thedataargument, and it can have undesirable effects, as explained here.
– eipi10
Nov 22 '18 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 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 '18 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 '18 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 at 13:37
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 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 theglmfunction with thedataargument, and it can have undesirable effects, as explained here.– eipi10
Nov 22 '18 at 17:00
thanks a lot - this solves my problem!
– rstarter
Nov 23 '18 at 13:37