setwd("c:/vidu")
library(foreign)
dulieu <- read.dta("muanha2.dta")
head(dulieu)## TIME GIADV NGANG DAI DTICH DTN KCACH MTIEN STHUONG XEHOI SLAU PHONG
## 1 1 0.10172414 6.8 7.0 116 12 10.5 1 0 0 2 3
## 2 2 0.05309735 10.0 20.0 226 12 10.5 1 0 0 1 3
## 3 3 0.11538462 6.0 10.0 52 7 11.0 0 1 0 3 3
## 4 4 0.09200000 5.0 20.0 100 20 10.6 1 1 0 2 3
## 5 5 0.05714286 8.5 13.5 112 6 6.8 1 1 1 3 4
## 6 6 0.08989899 5.3 18.7 99 10 5.7 1 0 0 2 3m0 <- lm(GIADV~.,data=dulieu)
m1 <- lm(GIADV~NGANG+DAI, data=dulieu)
m2 <- lm(GIADV~NGANG + DAI + DTICH + KCACH, data=dulieu)
m3 <- lm(GIADV~NGANG + DAI + DTICH + KCACH + MTIEN + STHUONG, data=dulieu)
m4 <- lm(GIADV~NGANG + DAI + DTICH + KCACH + MTIEN + STHUONG +SLAU +PHONG, data=dulieu)
library(stargazer)##
## Please cite as:## Hlavac, Marek (2018). stargazer: Well-Formatted Regression and Summary Statistics Tables.## R package version 5.2.2. https://CRAN.R-project.org/package=stargazerstargazer(m1, m2, m3, m4, type="text")##
## ================================================================================================================
## Dependent variable:
## --------------------------------------------------------------------------------------------
## GIADV
## (1) (2) (3) (4)
## ----------------------------------------------------------------------------------------------------------------
## NGANG -0.001 0.006* 0.003 0.002
## (0.003) (0.003) (0.003) (0.003)
##
## DAI 0.002* 0.003** 0.002* 0.001
## (0.001) (0.001) (0.001) (0.001)
##
## DTICH -0.0005*** -0.0005*** -0.0005***
## (0.0001) (0.0001) (0.0001)
##
## KCACH -0.025*** -0.023*** -0.021***
## (0.001) (0.001) (0.001)
##
## MTIEN 0.063*** 0.058***
## (0.011) (0.011)
##
## STHUONG -0.013 -0.017
## (0.012) (0.012)
##
## SLAU 0.007**
## (0.003)
##
## PHONG 0.018
## (0.014)
##
## Constant 0.188*** 0.358*** 0.325*** 0.247***
## (0.023) (0.026) (0.026) (0.049)
##
## ----------------------------------------------------------------------------------------------------------------
## Observations 998 998 998 994
## R2 0.003 0.349 0.370 0.386
## Adjusted R2 0.001 0.346 0.366 0.381
## Residual Std. Error 0.222 (df = 995) 0.180 (df = 993) 0.177 (df = 991) 0.175 (df = 985)
## F Statistic 1.596 (df = 2; 995) 133.155*** (df = 4; 993) 97.106*** (df = 6; 991) 77.439*** (df = 8; 985)
## ================================================================================================================
## Note: *p<0.1; **p<0.05; ***p<0.01anova(m1, m2, m3)## Analysis of Variance Table
##
## Model 1: GIADV ~ NGANG + DAI
## Model 2: GIADV ~ NGANG + DAI + DTICH + KCACH
## Model 3: GIADV ~ NGANG + DAI + DTICH + KCACH + MTIEN + STHUONG
## Res.Df RSS Df Sum of Sq F Pr(>F)
## 1 995 49.094
## 2 993 32.057 2 17.0371 272.176 < 2.2e-16 ***
## 3 991 31.016 2 1.0408 16.627 7.897e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1