# Definindo as variáveis (Tr é o grupo, Y é o escore de cada subescala, X são as variáveis independentes)
Tr <- cbind(Grupo)
Ypreocupacao <- cbind(Preocupacao)
Ycontrole <- cbind(Controle)
Yconfianca <- cbind(Confiança)
Ycooperacao <- cbind(Cooperacao)
Ycolaboration <- cbind(Colaboration)
Ytask <- cbind(Task_Performance)
Yemotional <- cbind(Emotional_Regulation)
Yengaging <- cbind(Engaging_With_Others)
Yopen <- cbind(Open_Mindedness)
X <- cbind(Idade, Renda, Residencia, Escolaridade_cuida, Ano)
# Variaveis para uso posterior
var1 <- Idade
var2 <- Residencia
var3 <- Renda
var4 <- Escolaridade_cuida
var5 <- Ano
var6 <- Periodo# Descritivas gerais, sem divisão por grupo
summary(Ypreocupacao)## Preocupacao
## Min. :1.833
## 1st Qu.:3.333
## Median :3.833
## Mean :3.773
## 3rd Qu.:4.333
## Max. :5.000summary(Ycontrole)## Controle
## Min. :1.667
## 1st Qu.:3.458
## Median :3.917
## Mean :3.870
## 3rd Qu.:4.500
## Max. :5.000summary(Yconfianca)## Confiança
## Min. :2.167
## 1st Qu.:3.500
## Median :4.000
## Mean :3.997
## 3rd Qu.:4.500
## Max. :5.000summary(Ycooperacao)## Cooperacao
## Min. :1.833
## 1st Qu.:3.500
## Median :4.000
## Mean :3.975
## 3rd Qu.:4.500
## Max. :5.000summary(Ycolaboration)## Colaboration
## Min. :3.000
## 1st Qu.:3.714
## Median :4.000
## Mean :4.032
## 3rd Qu.:4.286
## Max. :5.000summary(Ytask)## Task_Performance
## Min. :2.600
## 1st Qu.:3.900
## Median :4.200
## Mean :4.206
## 3rd Qu.:4.500
## Max. :5.100summary(Yemotional)## Emotional_Regulation
## Min. :1.833
## 1st Qu.:3.167
## Median :3.667
## Mean :3.679
## 3rd Qu.:4.167
## Max. :5.167summary(Yengaging)## Engaging_With_Others
## Min. :2.000
## 1st Qu.:3.500
## Median :4.000
## Mean :4.003
## 3rd Qu.:4.500
## Max. :5.000summary(Yopen)## Open_Mindedness
## Min. :2.167
## 1st Qu.:3.667
## Median :4.000
## Mean :3.945
## 3rd Qu.:4.333
## Max. :5.000summary(X)## Idade Renda Residencia Escolaridade_cuida
## Min. :14.00 Min. :1.000 Min. :1.0 Min. :1.00
## 1st Qu.:16.00 1st Qu.:2.000 1st Qu.:1.0 1st Qu.:2.00
## Median :17.00 Median :2.000 Median :1.0 Median :4.00
## Mean :16.57 Mean :2.215 Mean :1.5 Mean :3.77
## 3rd Qu.:17.00 3rd Qu.:3.000 3rd Qu.:2.0 3rd Qu.:5.00
## Max. :19.00 Max. :4.000 Max. :3.0 Max. :7.00
## Ano
## Min. :1.0
## 1st Qu.:2.0
## Median :3.0
## Mean :2.5
## 3rd Qu.:3.0
## Max. :4.0# Propensity score model
glm1 <- glm(Tr ~ X, family=binomial(link = "probit"), data=mydata)
summary(glm1)##
## Call:
## glm(formula = Tr ~ X, family = binomial(link = "probit"), data = mydata)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -3.12273 -0.74677 -0.00399 0.83995 1.73597
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -15.65786 2.09992 -7.456 8.89e-14 ***
## XIdade 0.99148 0.13946 7.109 1.17e-12 ***
## XRenda -0.04931 0.15694 -0.314 0.753
## XResidencia -0.11530 0.16863 -0.684 0.494
## XEscolaridade_cuida -0.07111 0.06680 -1.065 0.287
## XAno -0.09424 0.17131 -0.550 0.582
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 277.26 on 199 degrees of freedom
## Residual deviance: 188.22 on 194 degrees of freedom
## AIC: 200.22
##
## Number of Fisher Scoring iterations: 6#library(MatchIt)
#install.packages("tidyr")
library(tidyr)
na.omit(mydata)## # A tibble: 176 x 88
## Protocolo Grupo Idade Sexo Residencia Renda Escolaridade_cu~ Ano
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 17 1 2 3 5 3
## 2 2 1 17 2 2 2 5 2
## 3 3 1 19 1 2 2 2 3
## 4 4 1 16 1 2 2 5 3
## 5 5 1 17 2 1 2 4 2
## 6 6 1 17 2 1 3 3 2
## 7 7 1 17 2 2 2 4 3
## 8 8 1 18 2 1 2 2 4
## 9 9 1 17 2 1 3 2 2
## 10 10 1 17 2 2 2 3 2
## # ... with 166 more rows, and 80 more variables: Periodo <dbl>,
## # CAAS_1 <dbl>, CAAS_2 <dbl>, CAAS_3 <dbl>, CAAS_4 <dbl>, CAAS_5 <dbl>,
## # CAAS_6 <dbl>, CAAS_7 <dbl>, CAAS_8 <dbl>, CAAS_9 <dbl>, CAAS_10 <dbl>,
## # CAAS_11 <dbl>, CAAS_12 <dbl>, CAAS_13 <dbl>, CAAS_14 <dbl>,
## # CAAS_15 <dbl>, CAAS_16 <dbl>, CAAS_17 <dbl>, CAAS_18 <dbl>,
## # CAAS_19 <dbl>, CAAS_20 <dbl>, CAAS_21 <dbl>, CAAS_22 <dbl>,
## # CAAS_23 <dbl>, CAAS_24 <dbl>, CAAS_28 <dbl>, CAAS_29 <dbl>,
## # CAAS_30 <dbl>, CAAS_31 <dbl>, CAAS_32 <dbl>, CAAS_33 <dbl>,
## # CAAS_34 <dbl>, SENNA_1_1 <dbl>, SENNA_1_2 <dbl>, SENNA_1_3 <dbl>,
## # SENNA_1_4 <dbl>, SENNA_1_5 <dbl>, SENNA_1_6 <dbl>, SENNA_1_7 <dbl>,
## # SENNA_1_8 <dbl>, SENNA_1_9 <dbl>, SENNA_1_10 <dbl>, SENNA_1_11 <dbl>,
## # SENNA_1_12 <dbl>, SENNA_1_13 <dbl>, SENNA_1_14 <dbl>,
## # SENNA_1_15 <dbl>, SENNA_1_16 <dbl>, SENNA_1_17 <dbl>,
## # SENNA_1_18 <dbl>, SENNA_1_19 <dbl>, SENNA_1_20 <dbl>,
## # SENNA_1_21 <dbl>, SENNA_1_22 <dbl>, SENNA_1_23 <dbl>,
## # SENNA_1_24 <dbl>, SENNA_1_25 <dbl>, SENNA_1_26 <dbl>,
## # SENNA_1_27 <dbl>, SENNA_1_28 <dbl>, SENNA_1_29 <dbl>,
## # SENNA_1_30 <dbl>, SENNA_1_31 <dbl>, SENNA_1_32 <dbl>,
## # SENNA_1_33 <dbl>, SENNA_1_34 <dbl>, SENNA_1_35 <dbl>,
## # SENNA_1_36 <dbl>, Preocupacao <dbl>, Controle <dbl>,
## # Curiosidade <dbl>, Confiança <dbl>, Cooperacao <dbl>,
## # Adaptabilidade_Geral <dbl>, Colaboration <dbl>,
## # Task_Performance <dbl>, Engaging_With_Others <dbl>,
## # Emotional_Regulation <dbl>, Open_Mindedness <dbl>,
## # Competencias_Geral <dbl>drop_na(mydata)## # A tibble: 176 x 88
## Protocolo Grupo Idade Sexo Residencia Renda Escolaridade_cu~ Ano
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 17 1 2 3 5 3
## 2 2 1 17 2 2 2 5 2
## 3 3 1 19 1 2 2 2 3
## 4 4 1 16 1 2 2 5 3
## 5 5 1 17 2 1 2 4 2
## 6 6 1 17 2 1 3 3 2
## 7 7 1 17 2 2 2 4 3
## 8 8 1 18 2 1 2 2 4
## 9 9 1 17 2 1 3 2 2
## 10 10 1 17 2 2 2 3 2
## # ... with 166 more rows, and 80 more variables: Periodo <dbl>,
## # CAAS_1 <dbl>, CAAS_2 <dbl>, CAAS_3 <dbl>, CAAS_4 <dbl>, CAAS_5 <dbl>,
## # CAAS_6 <dbl>, CAAS_7 <dbl>, CAAS_8 <dbl>, CAAS_9 <dbl>, CAAS_10 <dbl>,
## # CAAS_11 <dbl>, CAAS_12 <dbl>, CAAS_13 <dbl>, CAAS_14 <dbl>,
## # CAAS_15 <dbl>, CAAS_16 <dbl>, CAAS_17 <dbl>, CAAS_18 <dbl>,
## # CAAS_19 <dbl>, CAAS_20 <dbl>, CAAS_21 <dbl>, CAAS_22 <dbl>,
## # CAAS_23 <dbl>, CAAS_24 <dbl>, CAAS_28 <dbl>, CAAS_29 <dbl>,
## # CAAS_30 <dbl>, CAAS_31 <dbl>, CAAS_32 <dbl>, CAAS_33 <dbl>,
## # CAAS_34 <dbl>, SENNA_1_1 <dbl>, SENNA_1_2 <dbl>, SENNA_1_3 <dbl>,
## # SENNA_1_4 <dbl>, SENNA_1_5 <dbl>, SENNA_1_6 <dbl>, SENNA_1_7 <dbl>,
## # SENNA_1_8 <dbl>, SENNA_1_9 <dbl>, SENNA_1_10 <dbl>, SENNA_1_11 <dbl>,
## # SENNA_1_12 <dbl>, SENNA_1_13 <dbl>, SENNA_1_14 <dbl>,
## # SENNA_1_15 <dbl>, SENNA_1_16 <dbl>, SENNA_1_17 <dbl>,
## # SENNA_1_18 <dbl>, SENNA_1_19 <dbl>, SENNA_1_20 <dbl>,
## # SENNA_1_21 <dbl>, SENNA_1_22 <dbl>, SENNA_1_23 <dbl>,
## # SENNA_1_24 <dbl>, SENNA_1_25 <dbl>, SENNA_1_26 <dbl>,
## # SENNA_1_27 <dbl>, SENNA_1_28 <dbl>, SENNA_1_29 <dbl>,
## # SENNA_1_30 <dbl>, SENNA_1_31 <dbl>, SENNA_1_32 <dbl>,
## # SENNA_1_33 <dbl>, SENNA_1_34 <dbl>, SENNA_1_35 <dbl>,
## # SENNA_1_36 <dbl>, Preocupacao <dbl>, Controle <dbl>,
## # Curiosidade <dbl>, Confiança <dbl>, Cooperacao <dbl>,
## # Adaptabilidade_Geral <dbl>, Colaboration <dbl>,
## # Task_Performance <dbl>, Engaging_With_Others <dbl>,
## # Emotional_Regulation <dbl>, Open_Mindedness <dbl>,
## # Competencias_Geral <dbl>#mydata %>% matchit(Tr ~ X, data=mydata, method = "full", discard = "none")
#complete.cases(mydata)Trocar o polo da residência???
# Tratamento sobre a aprendizagem
rrpreocupacao <- Match(Y = Ypreocupacao, Tr = Tr, X = glm1$fitted)
rrcontrole <- Match(Y = Ycontrole, Tr = Tr, X = glm1$fitted)
rrconfianca <- Match(Y = Yconfianca, Tr = Tr, X = glm1$fitted)
rrcooperacao <- Match(Y = Ycooperacao, Tr = Tr, X = glm1$fitted)
rrcolaboration <- Match(Y = Ycolaboration, Tr = Tr, X = glm1$fitted)
rrtask <- Match(Y = Ytask, Tr = Tr, X = glm1$fitted)
rremotional <- Match(Y = Yemotional, Tr = Tr, X = glm1$fitted)
rrengaging <- Match(Y = Yengaging, Tr = Tr, X = glm1$fitted)
rropen <- Match(Y = Yopen, Tr = Tr, X = glm1$fitted)summary(rrpreocupacao)##
## Estimate... 0.48339
## AI SE...... 0.16792
## T-stat..... 2.8786
## p.val...... 0.0039942
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrcontrole)##
## Estimate... 0.25028
## AI SE...... 0.13683
## T-stat..... 1.8291
## p.val...... 0.067379
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrconfianca)##
## Estimate... 0.42411
## AI SE...... 0.13695
## T-stat..... 3.0968
## p.val...... 0.0019564
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrcooperacao)##
## Estimate... 0.39772
## AI SE...... 0.1497
## T-stat..... 2.6568
## p.val...... 0.0078878
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrcolaboration)##
## Estimate... 0.30986
## AI SE...... 0.099738
## T-stat..... 3.1067
## p.val...... 0.0018917
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrtask)##
## Estimate... 0.4358
## AI SE...... 0.11385
## T-stat..... 3.8278
## p.val...... 0.00012931
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rremotional)##
## Estimate... 0.393
## AI SE...... 0.16816
## T-stat..... 2.3371
## p.val...... 0.019434
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rrengaging)##
## Estimate... 0.092833
## AI SE...... 0.15373
## T-stat..... 0.60387
## p.val...... 0.54593
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152summary(rropen)##
## Estimate... 0.46867
## AI SE...... 0.13122
## T-stat..... 3.5717
## p.val...... 0.0003547
##
## Original number of observations.............. 200
## Original number of treated obs............... 100
## Matched number of observations............... 100
## Matched number of observations (unweighted). 152