library(readxl)
library(readxl)
datamod2 <- read_excel("C:/Users/Isabella/Desktop/datamod2.xlsx", 
    col_types = c("numeric", "text", "text", 
        "text", "text", "text", "text"))
mod=glm(formula= Z~NECESIDAD, family="binomial", data = datamod2)
summary(mod)
## 
## Call:
## glm(formula = Z ~ NECESIDAD, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.1790  -1.1790  -0.3735   1.1758   2.3228  
## 
## Coefficients:
##              Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  0.003824   0.087454   0.044    0.965    
## NECESIDAD1  -2.631832   0.300211  -8.767   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 820.28  on 714  degrees of freedom
## AIC: 824.28
## 
## Number of Fisher Scoring iterations: 5
mod2=glm(formula= Z~CAPACIDAD, family="binomial", data = datamod2)
summary(mod2)
## 
## Call:
## glm(formula = Z ~ CAPACIDAD, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -0.9921  -0.9921  -0.9921   1.3748   2.1899  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept) -0.45298    0.07726  -5.863 4.55e-09 ***
## CAPACIDAD1  -1.84961    1.05144  -1.759   0.0786 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 948.78  on 714  degrees of freedom
## AIC: 952.78
## 
## Number of Fisher Scoring iterations: 4
mod3=glm(formula= Z~AVERSION, family="binomial", data = datamod2)
summary(mod3)
## 
## Call:
## glm(formula = Z ~ AVERSION, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##    Min      1Q  Median      3Q     Max  
## -1.006  -1.006  -1.006   1.360   1.360  
## 
## Coefficients:
##              Estimate Std. Error z value Pr(>|z|)    
## (Intercept)  -0.41871    0.07764  -5.393 6.94e-08 ***
## AVERSION1   -16.14736  500.33967  -0.032    0.974    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 930.98  on 714  degrees of freedom
## AIC: 934.98
## 
## Number of Fisher Scoring iterations: 15
mod4=glm(formula= Z~EDUCACION, family="binomial", data = datamod2)
summary(mod4)
## 
## Call:
## glm(formula = Z ~ EDUCACION, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##    Min      1Q  Median      3Q     Max  
## -1.000  -1.000  -1.000   1.365   2.448  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept) -0.43188    0.07758  -5.567  2.6e-08 ***
## EDUCACION1  -2.51256    1.02885  -2.442   0.0146 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 941.09  on 714  degrees of freedom
## AIC: 945.09
## 
## Number of Fisher Scoring iterations: 5
mod5=glm(formula= Z~REQUISITOS, family="binomial", data = datamod2)
summary(mod5)
## 
## Call:
## glm(formula = Z ~ REQUISITOS, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -0.9951  -0.9951  -0.9951   1.3714   1.8465  
## 
## Coefficients:
##             Estimate Std. Error z value Pr(>|z|)    
## (Intercept) -0.44525    0.07781  -5.722 1.05e-08 ***
## REQUISITOS1 -1.05882    0.55822  -1.897   0.0579 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 949.39  on 714  degrees of freedom
## AIC: 953.39
## 
## Number of Fisher Scoring iterations: 4
mod4=glm(formula= Z~NECESIDAD+EDUCACION+AVERSION+REQUISITOS+CAPACIDAD, family="binomial", data = datamod2)
summary(mod4)
## 
## Call:
## glm(formula = Z ~ NECESIDAD + EDUCACION + AVERSION + REQUISITOS + 
##     CAPACIDAD, family = "binomial", data = datamod2)
## 
## Deviance Residuals: 
##     Min       1Q   Median       3Q      Max  
## -1.3041  -1.3041  -0.3735   1.0558   2.4478  
## 
## Coefficients:
##              Estimate Std. Error z value Pr(>|z|)    
## (Intercept)   0.29290    0.09561   3.063  0.00219 ** 
## NECESIDAD1   -2.92091    0.30269  -9.650  < 2e-16 ***
## EDUCACION1   -3.23734    1.03042  -3.142  0.00168 ** 
## AVERSION1   -16.85897  500.33967  -0.034  0.97312    
## REQUISITOS1  -1.79698    0.56098  -3.203  0.00136 ** 
## CAPACIDAD1   -2.59549    1.05316  -2.464  0.01372 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## (Dispersion parameter for binomial family taken to be 1)
## 
##     Null deviance: 953.75  on 715  degrees of freedom
## Residual deviance: 740.94  on 710  degrees of freedom
## AIC: 752.94
## 
## Number of Fisher Scoring iterations: 15