Tabla de Regresion - Diego Lara Chuquilin
link="https://docs.google.com/spreadsheets/d/e/2PACX-1vRq_z7dcVQae82F92aErK8S6f3Tv0E0hI_8tiNFRqRy3Lp4gyj0Tf8HCcBSWeboQgCquoB4D56DhOdx/pub?output=csv"
midata=read.csv(link, stringsAsFactors = F)
install.packages("papeR")## Installing package into '/home/rstudio-user/R/x86_64-pc-linux-gnu-library/4.0'
## (as 'lib' is unspecified)library(papeR)## Loading required package: car## Loading required package: carData## Loading required package: xtable## Registered S3 method overwritten by 'papeR':
## method from
## Anova.lme car##
## Attaching package: 'papeR'## The following object is masked from 'package:utils':
##
## toLatexsummary(midata)## poblacioncienmil nbi consejocomunal priorizado
## Min. : 0.00158 Min. : 5.36 Min. :0.00000 Min. :0.0000
## 1st Qu.: 0.07422 1st Qu.:28.35 1st Qu.:0.00000 1st Qu.:0.0000
## Median : 0.13998 Median :41.30 Median :0.00000 Median :0.0000
## Mean : 0.40470 Mean :42.96 Mean :0.05474 Mean :0.2518
## 3rd Qu.: 0.26255 3rd Qu.:55.48 3rd Qu.:0.00000 3rd Qu.:1.0000
## Max. :69.26836 Max. :98.81 Max. :1.00000 Max. :1.0000
## NA's :30
## uribista ejecucion apropiaciondolar pctopo
## Min. :0.0000 Min. :0.00000 Min. : 0.000 Min. : 0.000
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.: 0.000 1st Qu.: 5.922
## Median :1.0000 Median :0.00000 Median : 0.000 Median :20.308
## Mean :0.6278 Mean :0.03741 Mean : 8.276 Mean :27.874
## 3rd Qu.:1.0000 3rd Qu.:0.00000 3rd Qu.: 9.385 3rd Qu.:45.711
## Max. :1.0000 Max. :1.00000 Max. :132.643 Max. :99.419
## NA's :204 NA's :7str(midata)## 'data.frame': 1096 obs. of 8 variables:
## $ poblacioncienmil: num 20.9155 0.2406 0.0398 0.0558 0.2723 ...
## $ nbi : num 12.2 33.8 28.5 33.1 27.1 ...
## $ consejocomunal : num 0 0 0 0 0 0 0 0 0 0 ...
## $ priorizado : num 0 1 0 0 0 0 0 0 1 0 ...
## $ uribista : num 0 1 1 1 1 1 1 1 1 NA ...
## $ ejecucion : num 0 0 0 0 0 0 0 0 0 0 ...
## $ apropiaciondolar: num 102.17 4.19 1.59 0 0 ...
## $ pctopo : num 14.82 14.51 15.08 6.15 47.31 ...newOrder=c("apropiaciondolar","pctopo","uribista","priorizado","consejocomunal","ejecucion","poblacioncienmil","nbi")
midata=midata[,newOrder]summary(midata)## apropiaciondolar pctopo uribista priorizado
## Min. : 0.000 Min. : 0.000 Min. :0.0000 Min. :0.0000
## 1st Qu.: 0.000 1st Qu.: 5.922 1st Qu.:0.0000 1st Qu.:0.0000
## Median : 0.000 Median :20.308 Median :1.0000 Median :0.0000
## Mean : 8.276 Mean :27.874 Mean :0.6278 Mean :0.2518
## 3rd Qu.: 9.385 3rd Qu.:45.711 3rd Qu.:1.0000 3rd Qu.:1.0000
## Max. :132.643 Max. :99.419 Max. :1.0000 Max. :1.0000
## NA's :7 NA's :204
## consejocomunal ejecucion poblacioncienmil nbi
## Min. :0.00000 Min. :0.00000 Min. : 0.00158 Min. : 5.36
## 1st Qu.:0.00000 1st Qu.:0.00000 1st Qu.: 0.07422 1st Qu.:28.35
## Median :0.00000 Median :0.00000 Median : 0.13998 Median :41.30
## Mean :0.05474 Mean :0.03741 Mean : 0.40470 Mean :42.96
## 3rd Qu.:0.00000 3rd Qu.:0.00000 3rd Qu.: 0.26255 3rd Qu.:55.48
## Max. :1.00000 Max. :1.00000 Max. :69.26836 Max. :98.81
## NA's :30str(midata)## 'data.frame': 1096 obs. of 8 variables:
## $ apropiaciondolar: num 102.17 4.19 1.59 0 0 ...
## $ pctopo : num 14.82 14.51 15.08 6.15 47.31 ...
## $ uribista : num 0 1 1 1 1 1 1 1 1 NA ...
## $ priorizado : num 0 1 0 0 0 0 0 0 1 0 ...
## $ consejocomunal : num 0 0 0 0 0 0 0 0 0 0 ...
## $ ejecucion : num 0 0 0 0 0 0 0 0 0 0 ...
## $ poblacioncienmil: num 20.9155 0.2406 0.0398 0.0558 0.2723 ...
## $ nbi : num 12.2 33.8 28.5 33.1 27.1 ...names(midata)## [1] "apropiaciondolar" "pctopo" "uribista" "priorizado"
## [5] "consejocomunal" "ejecucion" "poblacioncienmil" "nbi"mipividaton=lm(apropiaciondolar~.,data=midata)
summary(mipividaton)##
## Call:
## lm(formula = apropiaciondolar ~ ., data = midata)
##
## Residuals:
## Min 1Q Median 3Q Max
## -60.201 -8.207 -5.875 2.505 92.488
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 14.13182 1.67651 8.429 < 2e-16 ***
## pctopo -0.03096 0.02126 -1.456 0.14563
## uribista -2.57184 1.09188 -2.355 0.01872 *
## priorizado -2.21395 1.18715 -1.865 0.06253 .
## consejocomunal 14.05017 2.32452 6.044 2.23e-09 ***
## ejecucion 2.95688 2.80758 1.053 0.29255
## poblacioncienmil 1.83866 0.20024 9.182 < 2e-16 ***
## nbi -0.09292 0.02941 -3.160 0.00163 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 15.38 on 868 degrees of freedom
## (220 observations deleted due to missingness)
## Multiple R-squared: 0.1751, Adjusted R-squared: 0.1684
## F-statistic: 26.32 on 7 and 868 DF, p-value: < 2.2e-16install.packages("stargazer")## Installing package into '/home/rstudio-user/R/x86_64-pc-linux-gnu-library/4.0'
## (as 'lib' is unspecified)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(mipividaton, title = "Resultados de la regresión lineal", dep.var.labels=c("Apropiación presupuestal"), covariate.labels=c("Población (100.000 habitantes)","Necesidades básicas insatisfechas","Consejo Comunal con Ejecución","Prioridad técnica","Alcaldes coalición uribista","Consejo Comunal con ejecución", "Porcentaje Votos oposición"))##
## % Table created by stargazer v.5.2.2 by Marek Hlavac, Harvard University. E-mail: hlavac at fas.harvard.edu
## % Date and time: Sun, Jul 05, 2020 - 23:31:58
## \begin{table}[!htbp] \centering
## \caption{Resultados de la regresión lineal}
## \label{}
## \begin{tabular}{@{\extracolsep{5pt}}lc}
## \\[-1.8ex]\hline
## \hline \\[-1.8ex]
## & \multicolumn{1}{c}{\textit{Dependent variable:}} \\
## \cline{2-2}
## \\[-1.8ex] & Apropiación presupuestal \\
## \hline \\[-1.8ex]
## Población (100.000 habitantes) & $-$0.031 \\
## & (0.021) \\
## & \\
## Necesidades básicas insatisfechas & $-$2.572$^{**}$ \\
## & (1.092) \\
## & \\
## Consejo Comunal con Ejecución & $-$2.214$^{*}$ \\
## & (1.187) \\
## & \\
## Prioridad técnica & 14.050$^{***}$ \\
## & (2.325) \\
## & \\
## Alcaldes coalición uribista & 2.957 \\
## & (2.808) \\
## & \\
## Consejo Comunal con ejecución & 1.839$^{***}$ \\
## & (0.200) \\
## & \\
## Porcentaje Votos oposición & $-$0.093$^{***}$ \\
## & (0.029) \\
## & \\
## Constant & 14.132$^{***}$ \\
## & (1.677) \\
## & \\
## \hline \\[-1.8ex]
## Observations & 876 \\
## R$^{2}$ & 0.175 \\
## Adjusted R$^{2}$ & 0.168 \\
## Residual Std. Error & 15.378 (df = 868) \\
## F Statistic & 26.316$^{***}$ (df = 7; 868) \\
## \hline
## \hline \\[-1.8ex]
## \textit{Note:} & \multicolumn{1}{r}{$^{*}$p$<$0.1; $^{**}$p$<$0.05; $^{***}$p$<$0.01} \\
## \end{tabular}
## \end{table}