wage1 <-
read.delim("wage1.txt")
attach(wage1)
result1 <-lm(wage~educ, data=wage1)
result2 <-lm(wage~educ+exper,
data=wage1)
result3
<-lm(wage~educ+I(educ^2)+exper+I(exper^2), data=wage1)
library(stargazer)
stargazer(result1,
result2, result3, type = "text")
===========================================================================================
Dependent variable:
-----------------------------------------------------------------------
wage
(1) (2) (3)
-------------------------------------------------------------------------------------------
educ 0.644*** 0.644*** -0.541**
(0.054) (0.054) (0.230)
I(educ2)
0.048***
(0.009)
exper 0.070*** 0.070*** 0.277***
(0.011) (0.011) (0.036)
I(exper2) -0.005***
(0.001)
Constant -3.391*** -3.391*** 2.354
(0.767) (0.767) (1.448)
-------------------------------------------------------------------------------------------
Observations 526 526 526
R2 0.225 0.225 0.304
Adjusted R2 0.222 0.222 0.298
Residual Std.
Error 3.257 (df = 523) 3.257 (df = 523) 3.094 (df = 521)
F Statistic 75.990*** (df = 2; 523) 75.990*** (df
= 2; 523) 56.774*** (df = 4; 521)
===========================================================================================
Note: *p<0.1; **p<0.05;
***p<0.01
Ahora,
solo cambiaremos algunos argumentos de la función stargazer.
-
type = "text",
Omitir este argumento del código anterior, ofrece el código latex de la tabla
de ecuación. ['latex' (default), 'html'
or 'text.']
-
keep.stat="n",
REstringre la cantidad de estadísticos del modelo colocados en la parte inferior
de la tabla.
-
single.row=FALSE,
coloca el error estándar de la regresión debajo o al lado del estadístico estimado
del modelo.
-
intercept.bottom=FALSE,
indica la parte de la tabla donde aparecerá el intercepto.
stargazer(result1,
result2, result3, header=FALSE,
type
= "text",
title="Tabla 1. Comparación de modelos",
keep.stat="n",digits=2, single.row=FALSE,
intercept.bottom=FALSE)
Tabla 1. Comparación de
modelos
==========================================
Dependent variable:
-----------------------------
wage
(1) (2) (3)
------------------------------------------
Constant
-3.39*** -3.39*** 2.35
(0.77) (0.77) (1.45)
educ
0.64*** 0.64*** -0.54**
(0.05) (0.05) (0.23)
I(educ2) 0.05***
(0.01)
exper
0.07*** 0.07*** 0.28***
(0.01) (0.01) (0.04)
I(exper2) -0.005***
(0.001)
------------------------------------------
Observations 526
526 526
==========================================
Note: *p<0.1; **p<0.05; ***p<0.01
stargazer(result1, result2, result3,
header=FALSE,
type
= "text",
title="Tabla 1. Comparación de modelos",
keep.stat="n",digits=2,
single.row=TRUE,
intercept.bottom=FALSE)
Tabla 1. Comparación de modelos
==============================================================
Dependent
variable:
-------------------------------------------------
wage
(1) (2) (3)
--------------------------------------------------------------
Constant
-3.39*** (0.77) -3.39*** (0.77)
2.35 (1.45)
educ 0.64*** (0.05) 0.64*** (0.05) -0.54** (0.23)
I(educ2) 0.05*** (0.01)
exper 0.07*** (0.01)
0.07*** (0.01) 0.28*** (0.04)
I(exper2) -0.005***
(0.001)
--------------------------------------------------------------
Observations
526 526 526
==============================================================
Note: *p<0.1;
**p<0.05; ***p<0.01
Utilizando el argumento covariate.labels, podemos cambiar el nombre de las
variables que aparecen en el cuadro.
stargazer(result1,
result2, result3, header=FALSE,
type = "text",
title="Tabla 1. Comparación de
modelos",
digits=2, single.row=FALSE,
intercept.bottom=TRUE,
covariate.labels=c("Educación","Educación2","Experiencia","Experiencia2"),
omit.stat=c("LL","ser","f")
)
Tabla 1. Comparación de modelos
==========================================
Dependent variable:
-----------------------------
wage
(1) (2) (3)
------------------------------------------
Educación
0.64*** 0.64*** -0.54**
(0.05) (0.05) (0.23)
Educación2 0.05***
(0.01)
Experiencia
0.07*** 0.07*** 0.28***
(0.01) (0.01) (0.04)
Experiencia2 -0.005***
(0.001)
Constant
-3.39*** -3.39*** 2.35
(0.77) (0.77) (1.45)
------------------------------------------
Observations
526 526 526
R2
0.23 0.23 0.30
Adjusted R2
0.22 0.22 0.30
==========================================
Note:
*p<0.1; **p<0.05; ***p<0.01
Pero,
el comando anterior, omite información sobre los residuos y la significancia
conjunta de las variables del modelo.
stargazer(result1, result2, result3, header=FALSE,
type =
"text",
title="Tabla 1. Comparación de
modelos",
digits=2, single.row=FALSE,
intercept.bottom=TRUE,
df = FALSE,
)
Tabla 1. Comparación de modelos
=================================================
Dependent
variable:
-----------------------------
wage
(1) (2) (3)
-------------------------------------------------
educ
0.64*** 0.64*** -0.54**
(0.05) (0.05) (0.23)
I(educ2) 0.05***
(0.01)
exper
0.07*** 0.07*** 0.28***
(0.01) (0.01) (0.04)
I(exper2) -0.005***
(0.001)
Constant
-3.39*** -3.39*** 2.35
(0.77) (0.77)
(1.45)
-------------------------------------------------
Observations
526 526 526
R2
0.23 0.23 0.30
Adjusted R2
0.22 0.22 0.30
Residual Std. Error
3.26 3.26 3.09
F Statistic
75.99*** 75.99*** 56.77***
=================================================
Note:
*p<0.1; **p<0.05; ***p<0.01
Adicionalmente,
podemos colocar el intervalo de confianza asociado a los coeficientes estimados,
a determinado nivel de confianza.
stargazer(result1, result2, result3,
header=FALSE,
type
= "text",
title="Tabla 1. Comparación de modelos",
digits=2,
single.row=FALSE,
intercept.bottom=TRUE,
omit.stat=c("LL","ser","f"),
ci=TRUE,
ci.level=0.90)
Tabla 1. Comparación de modelos
==========================================================
Dependent
variable:
---------------------------------------------
wage
(1) (2)
(3)
----------------------------------------------------------
educ
0.64*** 0.64*** -0.54**
(0.56, 0.73) (0.56, 0.73) (-0.92, -0.16)
I(educ2)
0.05***
(0.03, 0.06)
exper
0.07*** 0.07*** 0.28***
(0.05, 0.09)
(0.05, 0.09) (0.22, 0.34)
I(exper2)
-0.005***
(-0.01, -0.004)
Constant
-3.39*** -3.39*** 2.35
(-4.65, -2.13) (-4.65, -2.13)
(-0.03, 4.74)
----------------------------------------------------------
Observations
526 526 526
R2
0.23 0.23 0.30
Adjusted R2
0.22 0.22 0.30
==========================================================
Note: *p<0.1;
**p<0.05; ***p<0.01
Se
puede, cambiar el estilo de las tablas.
stargazer(result1,
result2, result3, header=FALSE,
type
= "text",
title="Tabla 1. Comparación de modelos",
digits=2,
single.row=FALSE,
intercept.bottom=TRUE,
omit.stat=c("LL","ser","f"),
style = "qje"
)
Tabla 1. Comparación de modelos
====================================================
wage
(1) (2) (3)
----------------------------------------------------
educ
0.64*** 0.64*** -0.54**
(0.05) (0.05) (0.23)
I(educ2) 0.05***
(0.01)
exper
0.07*** 0.07*** 0.28***
(0.01)
(0.01) (0.04)
I(exper2) -0.005***
(0.001)
Constant
-3.39*** -3.39*** 2.35
(0.77) (0.77) (1.45)
N
526 526 526
R2
0.23 0.23 0.30
Adjusted R2
0.22 0.22 0.30
====================================================
Notes:
***Significant at the 1 percent level.
**Significant at the 5 percent level.
*Significant at the 10 percent level.
Colocando
el nombre a los modelos en las tablas:
stargazer(result1,
result2, result3, header=FALSE,
type = "text",
title="Tabla 1. Comparación de
modelos",
digits=2, single.row=FALSE,
intercept.bottom=TRUE,
omit.stat=c("LL","ser","f"),
column.labels =
c("Model1", "Model2", "Model3")
)
Tabla 1. Comparación de modelos
==========================================
Dependent variable:
-----------------------------
wage
Model1 Model2 Model3
(1) (2)
(3)
------------------------------------------
educ
0.64*** 0.64*** -0.54**
(0.05) (0.05) (0.23)
I(educ2) 0.05***
(0.01)
exper
0.07*** 0.07*** 0.28***
(0.01) (0.01) (0.04)
I(exper2) -0.005***
(0.001)
Constant
-3.39*** -3.39*** 2.35
(0.77) (0.77) (1.45)
------------------------------------------
Observations
526 526 526
R2
0.23 0.23 0.30
Adjusted R2
0.22 0.22 0.30
==========================================
Note:
*p<0.1; **p<0.05; ***p<0.01
Referencias
Hlavac,
Marek (2015). stargazer: Well-Formatted Regression and Summary Statistics
Tables. R package version 5.2. http://CRAN.R-project.org/package=stargazer
Hlavac,
Marek (2015). stargazer: beautiful LATEX, HTML and ASCII tables from R
statistical output. Harvard University. Consultado en 2/12/2017.
Jake (nd). Stargazer. Consultado en 2/12/2017.
https://www.jakeruss.com/cheatsheets/stargazer/
Torres,
O. (2014). Using stargazer to report regression output and descriptive
statistics in R. (for non-LaTeX users). Pricenton
University. Consultado en 2/12/2017. https://www.princeton.edu/~otorres/NiceOutputR.pdf
