I've been using stargazer to display linear regression results (DID) specifically but there doesn't seem to be a command to allow me to find the mean of the dependent variable of the regression - say along with R^2 or a similar statistic.
I can't link the data - but here's one example of where I would like this stat.
mother_employ <- felm(paid_employment ~ treat + is_post + treated_group + age_dv + age_dv^2 + marital_status + educ_levels + nkids_dv + regions + white | year |0|pidp, subset = sex_dv == 2, data)
Below I display the regression results using stargazer - I've tried to put "mean" in the keep stat call without results
stargazer(employ_mother, title = "Mother Employment",
font.size = "small",
align = TRUE,
column.sep.width = "-15pt",keep.stat = c("adj.rsq","n"), keep = c("treat","is_post","treated_group","age_dv","age_dv^2","nkids_dv","white"), notes = "This Table Exludes Marital Status, Education Level, and Regions Covariates", type = "text")
My output is such:
Mother Employ
========================================================================================
Dependent variable:
--------------------------------------------------------------------------
paid_employment
----------------------------------------------------------------------------------------
treat 0.082***
(0.013)
is_post1 0.011
(0.012)
treated_group -0.352***
(0.010)
age_dv 0.008***
(0.0004)
nkids_dv -0.061***
(0.004)
white 0.168***
(0.010)
----------------------------------------------------------------------------------------
Observations 51,528
Adjusted R2 0.237
========================================================================================
Note: *p<0.1; **p<0.05; ***p<0.01
This Table Exludes Marital Status, Education Level, and Regions Covariates
>
I want to display the mean of the dependent variable with R^2 is this possible?
This is possible using the add.lines argument of stargazer().
library(stargazer)
model_results <- lm(mpg ~ cyl + drat, mtcars)
stargazer(model_results,
title = "Cars",
font.size = "small",
align = TRUE,
column.sep.width = "-15pt",
keep.stat = c("adj.rsq","n"),
add.lines = list("Mean" = c("Mean", mean(mtcars$mpg))),
out = "test.txt")
Gives us
Cars
========================================
Dependent variable:
---------------------------
mpg
----------------------------------------
cyl -2.484***
(0.447)
drat 1.872
(1.494)
Constant 28.725***
(7.592)
----------------------------------------
Mean 20.090625
Observations 32
Adjusted R2 0.722
========================================
Note: *p<0.1; **p<0.05; ***p<0.01
Alternatively, if we only want values that are used in the regression we can use.
mean(model_results$data$mpg) # For models from lm()
mean(model_results$response) # For models from felm()
In place of mean(mtcars$mpg)