Cálculos de Índices y Fiabilidad de las Escalas

Importar base de datos y paquete de Cálculos psicométricos

library(foreign, pos = 4)
library(Rcmdr)

## Loading required package: splines
## The Commander GUI is launched only in interactive sessions

library(psych)
investigacion <- read.spss("D:/cosas/Facultad/2014/investigación/gamingDB.sav", 
    use.value.labels = FALSE, to.data.frame = TRUE)

Calculos para Online Gaming Scale

Análisis de confiabilidad

# Escala de Logro
reliability(cov(investigacion[, c("vg9", "vg10", "vg11", "vg12")], use = "complete.obs"))

## Alpha reliability =  0.8351 
## Standardized alpha =  0.8367 
## 
## Reliability deleting each item in turn:
##       Alpha Std.Alpha r(item, total)
## vg9  0.7428    0.7438         0.7763
## vg10 0.7613    0.7634         0.7335
## vg11 0.7790    0.7809         0.6928
## vg12 0.8705    0.8713         0.4805

# Escala de Sociabilidad
reliability(cov(investigacion[, c("vg1", "vg2", "vg3", "vg4")], use = "complete.obs"))

## Alpha reliability =  0.5662 
## Standardized alpha =  0.5673 
## 
## Reliability deleting each item in turn:
##      Alpha Std.Alpha r(item, total)
## vg1 0.4602    0.4616         0.3890
## vg2 0.5782    0.5797         0.2412
## vg3 0.3424    0.3430         0.5339
## vg4 0.5637    0.5650         0.2580

# Escala de Presencia
reliability(cov(investigacion[, c("vg5", "vg6", "vg7", "vg8")], use = "complete.obs"))

## Alpha reliability =  0.5188 
## Standardized alpha =  0.5213 
## 
## Reliability deleting each item in turn:
##      Alpha Std.Alpha r(item, total)
## vg5 0.5360    0.5297         0.2112
## vg6 0.3756    0.3748         0.3840
## vg7 0.4727    0.4820         0.2777
## vg8 0.3904    0.3966         0.3732

Análisis Factorial

factorial <- investigacion[, c(5:16)]
# Varimax con 3 componentes
fit <- factanal(factorial, 3, rotation = "varimax")
print(fit, digits = 2, cutoff = 0.25, sort = TRUE)

## 
## Call:
## factanal(x = factorial, factors = 3, rotation = "varimax")
## 
## Uniquenesses:
##  vg1  vg2  vg3  vg4  vg5  vg6  vg7  vg8  vg9 vg10 vg11 vg12 
## 0.63 0.80 0.31 0.89 0.64 0.28 0.79 0.58 0.08 0.39 0.23 0.73 
## 
## Loadings:
##      Factor1 Factor2 Factor3
## vg9   0.96                  
## vg10  0.74                  
## vg11  0.74            0.47  
## vg12  0.51                  
## vg1           0.60          
## vg3           0.80          
## vg5           0.52          
## vg6                   0.83  
## vg8   0.30            0.58  
## vg2           0.36          
## vg4           0.33          
## vg7           0.30    0.33  
## 
##                Factor1 Factor2 Factor3
## SS loadings       2.45    1.66    1.52
## Proportion Var    0.20    0.14    0.13
## Cumulative Var    0.20    0.34    0.47
## 
## Test of the hypothesis that 3 factors are sufficient.
## The chi square statistic is 28.02 on 33 degrees of freedom.
## The p-value is 0.713