Actividad 3. Aplicación de modelos de ecuaciones estructurales (actividad individual)
Anna Durán A01285674 Osvaldo Tello - A01285642 Alma Santiago - A00836636 Rafaella Pérez - A00837142 Nancy Marroquín - A01198553
2026-02-23
Instalar librerias
library(readxl)
#install.packages("lavaan")
library(lavaan)## This is lavaan 0.6-21
## lavaan is FREE software! Please report any bugs.#install.packages("lavaanPlot")
library(lavaanPlot)Importar Base de Datos
df <- read_excel("C:\\Users\\almai\\Downloads\\Datos_SEM_Eng.xlsx")file.choose() # Entender la base de datos
summary(df)## ID GEN EXPER EDAD
## Min. : 1.0 Min. :0.0000 Min. : 0.00 Min. :22.00
## 1st Qu.: 56.5 1st Qu.:0.0000 1st Qu.:15.00 1st Qu.:37.50
## Median :112.0 Median :1.0000 Median :20.00 Median :44.00
## Mean :112.0 Mean :0.5919 Mean :21.05 Mean :43.95
## 3rd Qu.:167.5 3rd Qu.:1.0000 3rd Qu.:27.50 3rd Qu.:51.00
## Max. :223.0 Max. :1.0000 Max. :50.00 Max. :72.00
## RPD01 RPD02 RPD03 RPD05 RPD06
## Min. :1.000 Min. :1.00 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:3.00 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:3.000
## Median :5.000 Median :4.00 Median :5.000 Median :5.000 Median :5.000
## Mean :4.596 Mean :4.09 Mean :4.789 Mean :4.327 Mean :4.798
## 3rd Qu.:6.000 3rd Qu.:6.00 3rd Qu.:7.000 3rd Qu.:6.000 3rd Qu.:7.000
## Max. :7.000 Max. :7.00 Max. :7.000 Max. :7.000 Max. :7.000
## RPD07 RPD08 RPD09 RPD10
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:2.000 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:2.500
## Median :4.000 Median :5.000 Median :5.000 Median :5.000
## Mean :3.794 Mean :4.735 Mean :4.466 Mean :4.435
## 3rd Qu.:5.500 3rd Qu.:7.000 3rd Qu.:6.000 3rd Qu.:6.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## RRE02 RRE03 RRE04 RRE05 RRE06
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.0
## 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:4.0
## Median :6.000 Median :6.000 Median :6.000 Median :6.000 Median :6.0
## Mean :5.691 Mean :5.534 Mean :5.668 Mean :5.623 Mean :5.3
## 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.0
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.0
## RRE07 RRE10 RMA02 RMA03
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:4.000 1st Qu.:5.000 1st Qu.:3.000 1st Qu.:3.000
## Median :6.000 Median :6.000 Median :4.000 Median :5.000
## Mean :5.305 Mean :5.664 Mean :4.215 Mean :4.377
## 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:6.000 3rd Qu.:6.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## RMA04 RMA05 RMA06 RMA07
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:5.000 1st Qu.:4.000
## Median :5.000 Median :5.000 Median :6.000 Median :5.000
## Mean :4.686 Mean :4.637 Mean :5.511 Mean :4.767
## 3rd Qu.:6.000 3rd Qu.:6.000 3rd Qu.:7.000 3rd Qu.:6.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## RMA08 RMA09 RMA10 RCO02 RCO03
## Min. :1.000 Min. :1.000 Min. :1.00 Min. :1.000 Min. :1.000
## 1st Qu.:4.000 1st Qu.:3.000 1st Qu.:3.00 1st Qu.:5.000 1st Qu.:5.000
## Median :5.000 Median :5.000 Median :5.00 Median :6.000 Median :6.000
## Mean :4.942 Mean :4.614 Mean :4.43 Mean :5.336 Mean :5.574
## 3rd Qu.:6.500 3rd Qu.:6.000 3rd Qu.:6.00 3rd Qu.:7.000 3rd Qu.:7.000
## Max. :7.000 Max. :7.000 Max. :7.00 Max. :7.000 Max. :7.000
## RCO04 RCO05 RCO06 RCO07
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:5.000
## Median :6.000 Median :6.000 Median :6.000 Median :6.000
## Mean :5.704 Mean :5.668 Mean :5.619 Mean :5.632
## 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## EN01 EN02 EN04 EN05
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :1.000
## 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:4.000
## Median :5.000 Median :6.000 Median :5.000 Median :5.000
## Mean :4.717 Mean :5.004 Mean :4.883 Mean :4.928
## 3rd Qu.:6.000 3rd Qu.:7.000 3rd Qu.:6.000 3rd Qu.:6.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## EN06 EN07 EN08 EVI01
## Min. :1.000 Min. :1.000 Min. :1.000 Min. :0.000
## 1st Qu.:3.000 1st Qu.:3.000 1st Qu.:4.000 1st Qu.:4.000
## Median :5.000 Median :5.000 Median :5.000 Median :5.000
## Mean :4.767 Mean :4.578 Mean :4.776 Mean :5.013
## 3rd Qu.:6.000 3rd Qu.:6.000 3rd Qu.:6.000 3rd Qu.:6.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## EVI02 EVI03 EDE01 EDE02
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:4.000 1st Qu.:4.000 1st Qu.:5.000 1st Qu.:5.000
## Median :6.000 Median :6.000 Median :6.000 Median :6.000
## Mean :5.076 Mean :4.973 Mean :5.305 Mean :5.543
## 3rd Qu.:6.000 3rd Qu.:6.000 3rd Qu.:7.000 3rd Qu.:7.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000
## EDE03 EAB01 EAB02 EAB03
## Min. :0.000 Min. :0.000 Min. :0.000 Min. :0.000
## 1st Qu.:6.000 1st Qu.:5.000 1st Qu.:5.000 1st Qu.:5.000
## Median :7.000 Median :6.000 Median :6.000 Median :6.000
## Mean :6.135 Mean :5.605 Mean :5.821 Mean :5.363
## 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000 3rd Qu.:7.000
## Max. :7.000 Max. :7.000 Max. :7.000 Max. :7.000str(df)## tibble [223 × 51] (S3: tbl_df/tbl/data.frame)
## $ ID : num [1:223] 1 2 3 4 5 6 7 8 9 10 ...
## $ GEN : num [1:223] 1 1 1 1 1 0 0 1 1 1 ...
## $ EXPER: num [1:223] 22 22 30 17 23 31 26 30 15 15 ...
## $ EDAD : num [1:223] 45 44 52 41 51 52 53 48 40 38 ...
## $ RPD01: num [1:223] 5 4 7 5 7 3 5 6 4 2 ...
## $ RPD02: num [1:223] 1 4 7 5 6 4 5 7 4 3 ...
## $ RPD03: num [1:223] 3 6 7 1 7 5 4 6 4 2 ...
## $ RPD05: num [1:223] 2 5 7 1 6 4 4 7 4 3 ...
## $ RPD06: num [1:223] 3 3 7 3 7 3 5 2 6 7 ...
## $ RPD07: num [1:223] 1 2 6 5 6 5 6 5 4 1 ...
## $ RPD08: num [1:223] 3 3 7 3 7 4 6 2 5 3 ...
## $ RPD09: num [1:223] 2 4 7 2 6 4 7 4 4 2 ...
## $ RPD10: num [1:223] 4 4 7 2 6 4 7 1 6 2 ...
## $ RRE02: num [1:223] 6 6 7 6 7 5 7 5 6 7 ...
## $ RRE03: num [1:223] 6 6 7 6 7 4 7 4 4 7 ...
## $ RRE04: num [1:223] 6 6 7 6 7 4 7 4 6 7 ...
## $ RRE05: num [1:223] 6 6 7 6 7 5 7 4 6 7 ...
## $ RRE06: num [1:223] 6 6 7 6 7 4 7 4 6 7 ...
## $ RRE07: num [1:223] 6 6 7 6 7 4 7 4 6 7 ...
## $ RRE10: num [1:223] 6 6 7 6 7 4 7 4 6 7 ...
## $ RMA02: num [1:223] 4 6 4 3 4 7 5 2 6 7 ...
## $ RMA03: num [1:223] 5 6 5 4 4 7 5 1 2 7 ...
## $ RMA04: num [1:223] 5 5 6 4 4 5 5 1 4 7 ...
## $ RMA05: num [1:223] 5 5 6 4 4 6 5 3 4 7 ...
## $ RMA06: num [1:223] 6 6 7 6 5 4 5 7 6 7 ...
## $ RMA07: num [1:223] 4 6 6 5 4 5 7 4 6 7 ...
## $ RMA08: num [1:223] 5 6 4 4 4 6 6 4 2 7 ...
## $ RMA09: num [1:223] 3 5 4 3 5 4 5 2 4 7 ...
## $ RMA10: num [1:223] 7 5 5 4 5 5 6 4 3 7 ...
## $ RCO02: num [1:223] 7 7 7 5 7 6 7 7 3 7 ...
## $ RCO03: num [1:223] 7 7 7 5 7 5 7 7 3 7 ...
## $ RCO04: num [1:223] 7 7 7 6 7 4 7 7 3 7 ...
## $ RCO05: num [1:223] 7 7 7 6 7 4 7 7 3 7 ...
## $ RCO06: num [1:223] 7 7 7 6 7 4 7 7 4 7 ...
## $ RCO07: num [1:223] 5 7 7 6 7 4 7 7 7 7 ...
## $ EN01 : num [1:223] 6 6 7 4 6 4 7 7 4 7 ...
## $ EN02 : num [1:223] 7 6 7 4 6 4 7 7 4 7 ...
## $ EN04 : num [1:223] 6 6 7 4 6 4 7 6 4 7 ...
## $ EN05 : num [1:223] 5 5 7 5 6 5 7 6 4 7 ...
## $ EN06 : num [1:223] 5 5 7 5 6 3 7 5 5 7 ...
## $ EN07 : num [1:223] 5 5 7 2 6 4 7 4 4 7 ...
## $ EN08 : num [1:223] 6 5 7 5 6 4 7 4 4 7 ...
## $ EVI01: num [1:223] 6 5 7 5 6 4 7 6 6 0 ...
## $ EVI02: num [1:223] 6 5 7 6 6 4 6 5 5 1 ...
## $ EVI03: num [1:223] 6 6 6 7 6 4 6 6 7 0 ...
## $ EDE01: num [1:223] 6 6 6 5 7 6 7 7 7 1 ...
## $ EDE02: num [1:223] 7 6 7 6 7 5 7 7 7 5 ...
## $ EDE03: num [1:223] 7 7 7 7 7 5 7 7 7 6 ...
## $ EAB01: num [1:223] 7 7 7 6 7 5 7 7 7 0 ...
## $ EAB02: num [1:223] 7 7 7 6 7 5 7 2 5 1 ...
## $ EAB03: num [1:223] 6 5 6 5 6 5 7 3 5 0 ...head(df)## # A tibble: 6 × 51
## ID GEN EXPER EDAD RPD01 RPD02 RPD03 RPD05 RPD06 RPD07 RPD08 RPD09 RPD10
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 1 1 22 45 5 1 3 2 3 1 3 2 4
## 2 2 1 22 44 4 4 6 5 3 2 3 4 4
## 3 3 1 30 52 7 7 7 7 7 6 7 7 7
## 4 4 1 17 41 5 5 1 1 3 5 3 2 2
## 5 5 1 23 51 7 6 7 6 7 6 7 6 6
## 6 6 0 31 52 3 4 5 4 3 5 4 4 4
## # ℹ 38 more variables: RRE02 <dbl>, RRE03 <dbl>, RRE04 <dbl>, RRE05 <dbl>,
## # RRE06 <dbl>, RRE07 <dbl>, RRE10 <dbl>, RMA02 <dbl>, RMA03 <dbl>,
## # RMA04 <dbl>, RMA05 <dbl>, RMA06 <dbl>, RMA07 <dbl>, RMA08 <dbl>,
## # RMA09 <dbl>, RMA10 <dbl>, RCO02 <dbl>, RCO03 <dbl>, RCO04 <dbl>,
## # RCO05 <dbl>, RCO06 <dbl>, RCO07 <dbl>, EN01 <dbl>, EN02 <dbl>, EN04 <dbl>,
## # EN05 <dbl>, EN06 <dbl>, EN07 <dbl>, EN08 <dbl>, EVI01 <dbl>, EVI02 <dbl>,
## # EVI03 <dbl>, EDE01 <dbl>, EDE02 <dbl>, EDE03 <dbl>, EAB01 <dbl>, …El cuestionario evalúa experiencias de recuperación fuera del
trabajo, energía recuperada y engagement laboral, todas medidas en
escalas tipo Likert de 1 a 7. Estructuralmente, las variables se agrupan
en dimensiones latentes bien definidas:
- Desapego psicológico (RPD): grado en que la persona
logra desconectarse mentalmente del trabajo fuera del horario
laboral.
- Relajación (RRE): actividades que reducen tensión y
estrés mediante descanso o esparcimiento.
- Maestría (RMA): experiencias retadoras y de
aprendizaje que amplían habilidades o perspectivas.
- Control (RCO): percepción de autonomía sobre cómo
organizar el tiempo fuera del trabajo.
- Energía recuperada (EN / REG): sensación subjetiva de
haber descansado y re-energizado.
- Engagement laboral (UWES): estado positivo
relacionado con el trabajo, compuesto por:
- Vigor (EVI): altos niveles de energía y resiliencia.
- Dedicación (EDE): entusiasmo, inspiración y orgullo.
- Absorción (EAB): concentración profunda e inmersión en el
trabajo.
Parte 1: Experiencias de Recuperación
modelo1 <- ' # variables latentes
desapego =~ RPD01 + RPD02 + RPD03 + RPD05 +
RPD06 + RPD07 + RPD08 + RPD09 + RPD10
relajacion =~ RRE02 + RRE03 + RRE04 + RRE05 +
RRE06 + RRE07 + RRE10
dominio =~ RMA02 + RMA03 + RMA04 + RMA05 +
RMA06 + RMA07 + RMA08 + RMA09 + RMA10
control =~ RCO02 + RCO03 + RCO04 + RCO05 +
RCO06 + RCO07
'# Análisis Factorial Confirmatorio
fit1 <- cfa(modelo1,df) # integra bd con el modelo
summary(fit1, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-21 ended normally after 56 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 68
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 1215.404
## Degrees of freedom 428
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 7522.157
## Degrees of freedom 465
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.888
## Tucker-Lewis Index (TLI) 0.879
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10613.334
## Loglikelihood unrestricted model (H1) -10005.632
##
## Akaike (AIC) 21362.669
## Bayesian (BIC) 21594.356
## Sample-size adjusted Bayesian (SABIC) 21378.856
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.091
## 90 Percent confidence interval - lower 0.085
## 90 Percent confidence interval - upper 0.097
## P-value H_0: RMSEA <= 0.050 0.000
## P-value H_0: RMSEA >= 0.080 0.998
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.071
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## desapego =~
## RPD01 1.000 1.388 0.789
## RPD02 1.204 0.081 14.786 0.000 1.670 0.857
## RPD03 1.143 0.085 13.420 0.000 1.586 0.798
## RPD05 1.310 0.086 15.269 0.000 1.818 0.877
## RPD06 1.086 0.088 12.282 0.000 1.507 0.745
## RPD07 1.227 0.085 14.451 0.000 1.702 0.843
## RPD08 1.163 0.086 13.487 0.000 1.614 0.801
## RPD09 1.315 0.087 15.175 0.000 1.825 0.873
## RPD10 1.345 0.088 15.290 0.000 1.866 0.878
## relajacion =~
## RRE02 1.000 1.275 0.850
## RRE03 1.120 0.065 17.268 0.000 1.427 0.871
## RRE04 1.024 0.058 17.732 0.000 1.306 0.883
## RRE05 1.055 0.056 18.798 0.000 1.345 0.910
## RRE06 1.243 0.074 16.857 0.000 1.585 0.859
## RRE07 1.115 0.071 15.687 0.000 1.422 0.824
## RRE10 0.815 0.067 12.135 0.000 1.038 0.698
## dominio =~
## RMA02 1.000 1.406 0.729
## RMA03 1.155 0.096 12.060 0.000 1.624 0.799
## RMA04 1.179 0.089 13.267 0.000 1.659 0.874
## RMA05 1.141 0.087 13.049 0.000 1.604 0.860
## RMA06 0.647 0.075 8.618 0.000 0.911 0.581
## RMA07 1.104 0.085 13.050 0.000 1.552 0.860
## RMA08 1.109 0.085 12.985 0.000 1.560 0.856
## RMA09 1.030 0.084 12.251 0.000 1.448 0.811
## RMA10 1.056 0.088 12.039 0.000 1.486 0.798
## control =~
## RCO02 1.000 1.631 0.855
## RCO03 0.948 0.049 19.230 0.000 1.546 0.912
## RCO04 0.795 0.044 18.125 0.000 1.297 0.886
## RCO05 0.817 0.043 18.981 0.000 1.332 0.906
## RCO06 0.834 0.046 18.247 0.000 1.360 0.889
## RCO07 0.834 0.046 18.078 0.000 1.361 0.884
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## desapego ~~
## relajacion 1.155 0.164 7.023 0.000 0.653 0.653
## dominio 0.696 0.155 4.477 0.000 0.357 0.357
## control 1.319 0.200 6.584 0.000 0.583 0.583
## relajacion ~~
## dominio 0.969 0.159 6.085 0.000 0.540 0.540
## control 1.483 0.195 7.610 0.000 0.713 0.713
## dominio ~~
## control 1.221 0.202 6.047 0.000 0.532 0.532
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .RPD01 1.168 0.119 9.778 0.000 1.168 0.378
## .RPD02 1.005 0.109 9.240 0.000 1.005 0.265
## .RPD03 1.434 0.147 9.728 0.000 1.434 0.363
## .RPD05 0.989 0.110 8.969 0.000 0.989 0.230
## .RPD06 1.817 0.182 9.968 0.000 1.817 0.444
## .RPD07 1.177 0.125 9.391 0.000 1.177 0.289
## .RPD08 1.454 0.150 9.710 0.000 1.454 0.358
## .RPD09 1.035 0.115 9.028 0.000 1.035 0.237
## .RPD10 1.033 0.115 8.956 0.000 1.033 0.229
## .RRE02 0.624 0.067 9.269 0.000 0.624 0.277
## .RRE03 0.651 0.072 9.005 0.000 0.651 0.242
## .RRE04 0.481 0.055 8.798 0.000 0.481 0.220
## .RRE05 0.373 0.046 8.147 0.000 0.373 0.171
## .RRE06 0.891 0.097 9.162 0.000 0.891 0.262
## .RRE07 0.953 0.100 9.511 0.000 0.953 0.320
## .RRE10 1.136 0.113 10.092 0.000 1.136 0.513
## .RMA02 1.742 0.175 9.934 0.000 1.742 0.468
## .RMA03 1.489 0.155 9.581 0.000 1.489 0.361
## .RMA04 0.854 0.097 8.772 0.000 0.854 0.237
## .RMA05 0.904 0.101 8.981 0.000 0.904 0.260
## .RMA06 1.627 0.158 10.279 0.000 1.627 0.662
## .RMA07 0.846 0.094 8.980 0.000 0.846 0.260
## .RMA08 0.885 0.098 9.035 0.000 0.885 0.267
## .RMA09 1.090 0.115 9.496 0.000 1.090 0.342
## .RMA10 1.258 0.131 9.590 0.000 1.258 0.363
## .RCO02 0.980 0.105 9.375 0.000 0.980 0.269
## .RCO03 0.482 0.057 8.379 0.000 0.482 0.168
## .RCO04 0.463 0.052 8.967 0.000 0.463 0.216
## .RCO05 0.385 0.045 8.536 0.000 0.385 0.178
## .RCO06 0.493 0.055 8.915 0.000 0.493 0.210
## .RCO07 0.516 0.057 8.987 0.000 0.516 0.218
## desapego 1.925 0.275 7.002 0.000 1.000 1.000
## relajacion 1.625 0.207 7.845 0.000 1.000 1.000
## dominio 1.978 0.317 6.241 0.000 1.000 1.000
## control 2.660 0.335 7.930 0.000 1.000 1.000lavaanPlot(model = fit1, coefs = TRUE, covs = TRUE)Parte 1: Segundo orden
recuperacion =~ desapego + relajacion + dominio + controlmodelo1_2orden <- '
desapego =~ RPD01 + RPD02 + RPD03 + RPD05 +
RPD06 + RPD07 + RPD08 + RPD09 + RPD10
relajacion =~ RRE02 + RRE03 + RRE04 + RRE05 +
RRE06 + RRE07 + RRE10
dominio =~ RMA02 + RMA03 + RMA04 + RMA05 +
RMA06 + RMA07 + RMA08 + RMA09 + RMA10
control =~ RCO02 + RCO03 + RCO04 + RCO05 +
RCO06 + RCO07
recuperacion =~ desapego + relajacion + dominio + control
'
fit1_2orden <- cfa(modelo1_2orden, df)
summary(fit1_2orden, fit.measures=TRUE, standardized=TRUE)## lavaan 0.6-21 ended normally after 47 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 66
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 1221.031
## Degrees of freedom 430
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 7522.157
## Degrees of freedom 465
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.888
## Tucker-Lewis Index (TLI) 0.879
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -10616.148
## Loglikelihood unrestricted model (H1) -10005.632
##
## Akaike (AIC) 21364.296
## Bayesian (BIC) 21589.169
## Sample-size adjusted Bayesian (SABIC) 21380.007
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.091
## 90 Percent confidence interval - lower 0.085
## 90 Percent confidence interval - upper 0.097
## P-value H_0: RMSEA <= 0.050 0.000
## P-value H_0: RMSEA >= 0.080 0.998
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.075
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## desapego =~
## RPD01 1.000 1.386 0.788
## RPD02 1.206 0.082 14.780 0.000 1.672 0.858
## RPD03 1.143 0.085 13.374 0.000 1.584 0.797
## RPD05 1.312 0.086 15.244 0.000 1.818 0.878
## RPD06 1.088 0.089 12.266 0.000 1.507 0.745
## RPD07 1.229 0.085 14.440 0.000 1.703 0.844
## RPD08 1.164 0.087 13.447 0.000 1.613 0.800
## RPD09 1.317 0.087 15.153 0.000 1.826 0.874
## RPD10 1.346 0.088 15.258 0.000 1.866 0.878
## relajacion =~
## RRE02 1.000 1.274 0.849
## RRE03 1.120 0.065 17.227 0.000 1.427 0.870
## RRE04 1.025 0.058 17.713 0.000 1.306 0.883
## RRE05 1.055 0.056 18.758 0.000 1.344 0.910
## RRE06 1.245 0.074 16.869 0.000 1.586 0.860
## RRE07 1.117 0.071 15.689 0.000 1.423 0.825
## RRE10 0.815 0.067 12.120 0.000 1.038 0.698
## dominio =~
## RMA02 1.000 1.407 0.730
## RMA03 1.155 0.096 12.079 0.000 1.626 0.800
## RMA04 1.178 0.089 13.274 0.000 1.658 0.873
## RMA05 1.141 0.087 13.072 0.000 1.606 0.861
## RMA06 0.645 0.075 8.597 0.000 0.908 0.579
## RMA07 1.103 0.084 13.061 0.000 1.552 0.860
## RMA08 1.109 0.085 12.994 0.000 1.560 0.856
## RMA09 1.028 0.084 12.246 0.000 1.447 0.810
## RMA10 1.055 0.088 12.044 0.000 1.485 0.798
## control =~
## RCO02 1.000 1.630 0.854
## RCO03 0.948 0.049 19.182 0.000 1.545 0.912
## RCO04 0.796 0.044 18.110 0.000 1.297 0.886
## RCO05 0.818 0.043 18.990 0.000 1.333 0.907
## RCO06 0.834 0.046 18.216 0.000 1.360 0.888
## RCO07 0.835 0.046 18.057 0.000 1.361 0.884
## recuperacion =~
## desapego 1.000 0.713 0.713
## relajacion 1.149 0.131 8.787 0.000 0.892 0.892
## dominio 0.858 0.129 6.666 0.000 0.603 0.603
## control 1.341 0.156 8.605 0.000 0.813 0.813
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .RPD01 1.172 0.120 9.782 0.000 1.172 0.379
## .RPD02 0.999 0.108 9.228 0.000 0.999 0.263
## .RPD03 1.441 0.148 9.733 0.000 1.441 0.365
## .RPD05 0.987 0.110 8.964 0.000 0.987 0.230
## .RPD06 1.817 0.182 9.967 0.000 1.817 0.444
## .RPD07 1.173 0.125 9.383 0.000 1.173 0.288
## .RPD08 1.460 0.150 9.714 0.000 1.460 0.360
## .RPD09 1.032 0.114 9.021 0.000 1.032 0.236
## .RPD10 1.034 0.115 8.955 0.000 1.034 0.229
## .RRE02 0.626 0.068 9.274 0.000 0.626 0.278
## .RRE03 0.653 0.073 9.011 0.000 0.653 0.243
## .RRE04 0.481 0.055 8.794 0.000 0.481 0.220
## .RRE05 0.374 0.046 8.153 0.000 0.374 0.172
## .RRE06 0.886 0.097 9.149 0.000 0.886 0.260
## .RRE07 0.950 0.100 9.505 0.000 0.950 0.319
## .RRE10 1.137 0.113 10.093 0.000 1.137 0.513
## .RMA02 1.740 0.175 9.931 0.000 1.740 0.468
## .RMA03 1.485 0.155 9.575 0.000 1.485 0.360
## .RMA04 0.855 0.097 8.772 0.000 0.855 0.237
## .RMA05 0.899 0.100 8.967 0.000 0.899 0.259
## .RMA06 1.631 0.159 10.281 0.000 1.631 0.664
## .RMA07 0.845 0.094 8.977 0.000 0.845 0.260
## .RMA08 0.886 0.098 9.034 0.000 0.886 0.267
## .RMA09 1.094 0.115 9.500 0.000 1.094 0.343
## .RMA10 1.259 0.131 9.590 0.000 1.259 0.363
## .RCO02 0.983 0.105 9.379 0.000 0.983 0.270
## .RCO03 0.484 0.058 8.391 0.000 0.484 0.169
## .RCO04 0.462 0.052 8.963 0.000 0.462 0.215
## .RCO05 0.382 0.045 8.513 0.000 0.382 0.177
## .RCO06 0.494 0.055 8.917 0.000 0.494 0.211
## .RCO07 0.515 0.057 8.985 0.000 0.515 0.218
## .desapego 0.943 0.152 6.207 0.000 0.491 0.491
## .relajacion 0.333 0.089 3.757 0.000 0.205 0.205
## .dominio 1.260 0.212 5.942 0.000 0.636 0.636
## .control 0.900 0.159 5.666 0.000 0.339 0.339
## recuperacion 0.978 0.202 4.833 0.000 1.000 1.000library(lavaanPlot)
lavaanPlot(
model = fit1_2orden,
coefs = TRUE,
stand = TRUE,
covs = FALSE,
graph_options = list(rankdir = "TB")
)Parte 2: Energía Recuperada
modelo2 <- ' # variables latentes
energia =~ EN01 + EN02 + EN04 + EN05 +
EN06 + EN07 + EN08
'# Análisis Factorial Confirmatorio
fit2 <- cfa(modelo2,df) # integra bd con el modelo
summary(fit2, fit.measures = TRUE, standardized = TRUE)## lavaan 0.6-21 ended normally after 32 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 14
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 47.222
## Degrees of freedom 14
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 2324.436
## Degrees of freedom 21
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.986
## Tucker-Lewis Index (TLI) 0.978
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -2017.154
## Loglikelihood unrestricted model (H1) -1993.543
##
## Akaike (AIC) 4062.308
## Bayesian (BIC) 4110.008
## Sample-size adjusted Bayesian (SABIC) 4065.641
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.103
## 90 Percent confidence interval - lower 0.072
## 90 Percent confidence interval - upper 0.136
## P-value H_0: RMSEA <= 0.050 0.004
## P-value H_0: RMSEA >= 0.080 0.892
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.012
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## energia =~
## EN01 1.000 1.674 0.893
## EN02 1.029 0.044 23.192 0.000 1.723 0.933
## EN04 0.999 0.044 22.583 0.000 1.672 0.924
## EN05 0.999 0.042 23.649 0.000 1.672 0.939
## EN06 0.986 0.042 23.722 0.000 1.651 0.940
## EN07 1.049 0.046 22.856 0.000 1.755 0.928
## EN08 1.036 0.043 24.173 0.000 1.734 0.946
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .EN01 0.711 0.074 9.651 0.000 0.711 0.202
## .EN02 0.444 0.049 9.012 0.000 0.444 0.130
## .EN04 0.481 0.052 9.214 0.000 0.481 0.147
## .EN05 0.375 0.042 8.830 0.000 0.375 0.118
## .EN06 0.359 0.041 8.798 0.000 0.359 0.116
## .EN07 0.499 0.055 9.129 0.000 0.499 0.139
## .EN08 0.353 0.041 8.580 0.000 0.353 0.105
## energia 2.801 0.327 8.565 0.000 1.000 1.000lavaanPlot(model = fit2, coefs = TRUE, covs = TRUE)Parte 3: Compromiso Laboral
modelo3 <- ' # variables latentes
vigor =~ EVI01 + EVI02 + EVI03
dedicacion =~ EDE01 + EDE02 + EDE03
absorcion =~ EAB01 + EAB02 + EAB03
'# Análisis Factorial Confirmatorio
fit3 <- cfa(modelo3,df) # integra bd con el modelo
summary(fit3, fit3.measures = TRUE, standardized = TRUE)## Warning: lavaan->.local():
## Unknown argument 'fit3.measures' for 'summary'## lavaan 0.6-21 ended normally after 44 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 21
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 271.168
## Degrees of freedom 24
## P-value (Chi-square) 0.000
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## vigor =~
## EVI01 1.000 1.684 0.967
## EVI02 0.986 0.028 35.166 0.000 1.660 0.962
## EVI03 0.995 0.049 20.456 0.000 1.675 0.835
## dedicacion =~
## EDE01 1.000 1.857 0.946
## EDE02 0.914 0.035 26.126 0.000 1.698 0.924
## EDE03 0.583 0.037 15.913 0.000 1.082 0.765
## absorcion =~
## EAB01 1.000 1.610 0.918
## EAB02 0.708 0.051 13.891 0.000 1.140 0.750
## EAB03 0.732 0.063 11.644 0.000 1.179 0.669
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## vigor ~~
## dedicacion 2.754 0.293 9.404 0.000 0.881 0.881
## absorcion 2.125 0.247 8.600 0.000 0.784 0.784
## dedicacion ~~
## absorcion 2.728 0.293 9.311 0.000 0.913 0.913
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .EVI01 0.200 0.040 4.947 0.000 0.200 0.066
## .EVI02 0.220 0.041 5.437 0.000 0.220 0.074
## .EVI03 1.220 0.125 9.772 0.000 1.220 0.303
## .EDE01 0.405 0.066 6.130 0.000 0.405 0.105
## .EDE02 0.495 0.066 7.521 0.000 0.495 0.146
## .EDE03 0.829 0.084 9.869 0.000 0.829 0.415
## .EAB01 0.481 0.100 4.816 0.000 0.481 0.157
## .EAB02 1.010 0.109 9.271 0.000 1.010 0.437
## .EAB03 1.711 0.175 9.764 0.000 1.711 0.552
## vigor 2.836 0.289 9.811 0.000 1.000 1.000
## dedicacion 3.448 0.367 9.399 0.000 1.000 1.000
## absorcion 2.592 0.301 8.615 0.000 1.000 1.000lavaanPlot(model = fit3, coefs = TRUE, covs = TRUE)modelo3 <- '
# Recuperación (segundo orden)
desapego =~ RPD01 + RPD02 + RPD03 + RPD05 +
RPD06 + RPD07 + RPD08 + RPD09 + RPD10
relajacion =~ RRE02 + RRE03 + RRE04 + RRE05 +
RRE06 + RRE07 + RRE10
dominio =~ RMA02 + RMA03 + RMA04 + RMA05 +
RMA06 + RMA07 + RMA08 + RMA09 + RMA10
control =~ RCO02 + RCO03 + RCO04 + RCO05 +
RCO06 + RCO07
recuperacion =~ desapego + relajacion + dominio + control
# Energía
energia =~ EN01 + EN02 + EN04 + EN05 +
EN06 + EN07 + EN08
# Engagement
vigor =~ EVI01 + EVI02 + EVI03
dedicacion =~ EDE01 + EDE02 + EDE03
absorcion =~ EAB01 + EAB02 + EAB03
engagement =~ vigor + dedicacion + absorcion
# Relaciones estructurales
energia ~ a*recuperacion
engagement ~ b*energia + c*recuperacion
# Efectos indirectos
indirecto := a*b
total := c + (a*b)
'
fit3 <- sem(modelo3, df)
summary(fit3, fit.measures=TRUE, standardized=TRUE, rsquare=TRUE)## lavaan 0.6-21 ended normally after 67 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 104
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 2501.954
## Degrees of freedom 1024
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 13350.303
## Degrees of freedom 1081
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.880
## Tucker-Lewis Index (TLI) 0.873
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -15454.903
## Loglikelihood unrestricted model (H1) -14203.926
##
## Akaike (AIC) 31117.805
## Bayesian (BIC) 31472.151
## Sample-size adjusted Bayesian (SABIC) 31142.562
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.080
## 90 Percent confidence interval - lower 0.076
## 90 Percent confidence interval - upper 0.084
## P-value H_0: RMSEA <= 0.050 0.000
## P-value H_0: RMSEA >= 0.080 0.578
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.074
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## desapego =~
## RPD01 1.000 1.387 0.789
## RPD02 1.209 0.081 14.865 0.000 1.677 0.861
## RPD03 1.144 0.085 13.419 0.000 1.587 0.798
## RPD05 1.313 0.086 15.317 0.000 1.822 0.879
## RPD06 1.082 0.089 12.214 0.000 1.501 0.742
## RPD07 1.229 0.085 14.487 0.000 1.705 0.845
## RPD08 1.157 0.086 13.375 0.000 1.604 0.796
## RPD09 1.315 0.087 15.163 0.000 1.824 0.873
## RPD10 1.343 0.088 15.247 0.000 1.863 0.877
## relajacion =~
## RRE02 1.000 1.275 0.850
## RRE03 1.120 0.065 17.295 0.000 1.429 0.871
## RRE04 1.021 0.058 17.625 0.000 1.301 0.880
## RRE05 1.051 0.056 18.687 0.000 1.341 0.908
## RRE06 1.246 0.074 16.924 0.000 1.588 0.861
## RRE07 1.121 0.071 15.838 0.000 1.430 0.829
## RRE10 0.814 0.067 12.134 0.000 1.038 0.698
## dominio =~
## RMA02 1.000 1.407 0.729
## RMA03 1.152 0.096 12.041 0.000 1.621 0.798
## RMA04 1.178 0.089 13.265 0.000 1.658 0.873
## RMA05 1.141 0.087 13.057 0.000 1.605 0.860
## RMA06 0.648 0.075 8.625 0.000 0.911 0.581
## RMA07 1.104 0.085 13.062 0.000 1.553 0.861
## RMA08 1.110 0.085 13.001 0.000 1.561 0.857
## RMA09 1.030 0.084 12.257 0.000 1.448 0.811
## RMA10 1.056 0.088 12.047 0.000 1.486 0.798
## control =~
## RCO02 1.000 1.632 0.855
## RCO03 0.945 0.049 19.172 0.000 1.543 0.910
## RCO04 0.794 0.044 18.100 0.000 1.295 0.884
## RCO05 0.814 0.043 18.926 0.000 1.329 0.904
## RCO06 0.837 0.045 18.407 0.000 1.365 0.892
## RCO07 0.836 0.046 18.205 0.000 1.364 0.887
## recuperacion =~
## desapego 1.000 0.711 0.711
## relajacion 1.070 0.121 8.840 0.000 0.827 0.827
## dominio 0.900 0.129 6.960 0.000 0.631 0.631
## control 1.423 0.157 9.062 0.000 0.860 0.860
## energia =~
## EN01 1.000 1.678 0.896
## EN02 1.027 0.044 23.415 0.000 1.723 0.933
## EN04 0.998 0.044 22.871 0.000 1.675 0.925
## EN05 0.996 0.042 23.836 0.000 1.671 0.939
## EN06 0.983 0.041 23.857 0.000 1.649 0.939
## EN07 1.045 0.045 22.963 0.000 1.753 0.926
## EN08 1.033 0.042 24.398 0.000 1.733 0.946
## vigor =~
## EVI01 1.000 1.684 0.967
## EVI02 0.985 0.028 35.282 0.000 1.659 0.962
## EVI03 0.996 0.048 20.546 0.000 1.677 0.836
## dedicacion =~
## EDE01 1.000 1.868 0.952
## EDE02 0.907 0.034 26.376 0.000 1.695 0.922
## EDE03 0.571 0.037 15.539 0.000 1.066 0.754
## absorcion =~
## EAB01 1.000 1.607 0.917
## EAB02 0.711 0.051 13.823 0.000 1.143 0.752
## EAB03 0.735 0.063 11.600 0.000 1.181 0.671
## engagement =~
## vigor 1.000 0.901 0.901
## dedicacion 1.213 0.061 19.812 0.000 0.985 0.985
## absorcion 0.958 0.059 16.371 0.000 0.904 0.904
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## energia ~
## recuperacn (a) 1.405 0.154 9.093 0.000 0.825 0.825
## engagement ~
## energia (b) 0.407 0.106 3.845 0.000 0.450 0.450
## recuperacn (c) 0.347 0.189 1.839 0.066 0.225 0.225
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .RPD01 1.168 0.119 9.781 0.000 1.168 0.378
## .RPD02 0.983 0.107 9.202 0.000 0.983 0.259
## .RPD03 1.434 0.147 9.729 0.000 1.434 0.363
## .RPD05 0.972 0.109 8.938 0.000 0.972 0.227
## .RPD06 1.836 0.184 9.980 0.000 1.836 0.449
## .RPD07 1.165 0.124 9.377 0.000 1.165 0.286
## .RPD08 1.486 0.153 9.740 0.000 1.486 0.366
## .RPD09 1.037 0.115 9.036 0.000 1.037 0.238
## .RPD10 1.046 0.116 8.984 0.000 1.046 0.232
## .RRE02 0.623 0.067 9.252 0.000 0.623 0.277
## .RRE03 0.647 0.072 8.976 0.000 0.647 0.241
## .RRE04 0.492 0.056 8.829 0.000 0.492 0.225
## .RRE05 0.384 0.047 8.203 0.000 0.384 0.176
## .RRE06 0.880 0.097 9.122 0.000 0.880 0.259
## .RRE07 0.930 0.098 9.460 0.000 0.930 0.313
## .RRE10 1.136 0.113 10.087 0.000 1.136 0.513
## .RMA02 1.741 0.175 9.935 0.000 1.741 0.468
## .RMA03 1.499 0.156 9.594 0.000 1.499 0.363
## .RMA04 0.857 0.098 8.785 0.000 0.857 0.238
## .RMA05 0.903 0.101 8.983 0.000 0.903 0.260
## .RMA06 1.626 0.158 10.280 0.000 1.626 0.662
## .RMA07 0.844 0.094 8.979 0.000 0.844 0.259
## .RMA08 0.882 0.098 9.031 0.000 0.882 0.266
## .RMA09 1.090 0.115 9.498 0.000 1.090 0.342
## .RMA10 1.257 0.131 9.592 0.000 1.257 0.363
## .RCO02 0.978 0.104 9.391 0.000 0.978 0.269
## .RCO03 0.493 0.058 8.474 0.000 0.493 0.172
## .RCO04 0.468 0.052 9.016 0.000 0.468 0.218
## .RCO05 0.393 0.046 8.621 0.000 0.393 0.182
## .RCO06 0.479 0.054 8.884 0.000 0.479 0.205
## .RCO07 0.505 0.056 8.972 0.000 0.505 0.213
## .EN01 0.696 0.072 9.660 0.000 0.696 0.198
## .EN02 0.443 0.049 9.064 0.000 0.443 0.130
## .EN04 0.473 0.051 9.236 0.000 0.473 0.144
## .EN05 0.378 0.042 8.907 0.000 0.378 0.119
## .EN06 0.366 0.041 8.899 0.000 0.366 0.119
## .EN07 0.507 0.055 9.209 0.000 0.507 0.142
## .EN08 0.353 0.041 8.658 0.000 0.353 0.105
## .EVI01 0.199 0.039 5.047 0.000 0.199 0.065
## .EVI02 0.224 0.040 5.620 0.000 0.224 0.075
## .EVI03 1.213 0.124 9.773 0.000 1.213 0.301
## .EDE01 0.363 0.065 5.605 0.000 0.363 0.094
## .EDE02 0.506 0.067 7.567 0.000 0.506 0.150
## .EDE03 0.864 0.087 9.921 0.000 0.864 0.432
## .EAB01 0.490 0.103 4.767 0.000 0.490 0.159
## .EAB02 1.003 0.109 9.186 0.000 1.003 0.434
## .EAB03 1.706 0.176 9.719 0.000 1.706 0.550
## .desapego 0.952 0.149 6.396 0.000 0.495 0.495
## .relajacion 0.514 0.085 6.023 0.000 0.316 0.316
## .dominio 1.191 0.200 5.956 0.000 0.602 0.602
## .control 0.694 0.125 5.538 0.000 0.261 0.261
## recuperacion 0.972 0.199 4.892 0.000 1.000 1.000
## .energia 0.898 0.137 6.565 0.000 0.319 0.319
## .vigor 0.536 0.085 6.327 0.000 0.189 0.189
## .dedicacion 0.102 0.090 1.143 0.253 0.029 0.029
## .absorcion 0.472 0.112 4.233 0.000 0.183 0.183
## .engagement 1.333 0.171 7.804 0.000 0.579 0.579
##
## R-Square:
## Estimate
## RPD01 0.622
## RPD02 0.741
## RPD03 0.637
## RPD05 0.773
## RPD06 0.551
## RPD07 0.714
## RPD08 0.634
## RPD09 0.762
## RPD10 0.768
## RRE02 0.723
## RRE03 0.759
## RRE04 0.775
## RRE05 0.824
## RRE06 0.741
## RRE07 0.687
## RRE10 0.487
## RMA02 0.532
## RMA03 0.637
## RMA04 0.762
## RMA05 0.740
## RMA06 0.338
## RMA07 0.741
## RMA08 0.734
## RMA09 0.658
## RMA10 0.637
## RCO02 0.731
## RCO03 0.828
## RCO04 0.782
## RCO05 0.818
## RCO06 0.795
## RCO07 0.787
## EN01 0.802
## EN02 0.870
## EN04 0.856
## EN05 0.881
## EN06 0.881
## EN07 0.858
## EN08 0.895
## EVI01 0.935
## EVI02 0.925
## EVI03 0.699
## EDE01 0.906
## EDE02 0.850
## EDE03 0.568
## EAB01 0.841
## EAB02 0.566
## EAB03 0.450
## desapego 0.505
## relajacion 0.684
## dominio 0.398
## control 0.739
## energia 0.681
## vigor 0.811
## dedicacion 0.971
## absorcion 0.817
## engagement 0.421
##
## Defined Parameters:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## indirecto 0.571 0.157 3.629 0.000 0.371 0.371
## total 0.918 0.130 7.038 0.000 0.597 0.597library(lavaanPlot)
lavaanPlot(
model = fit3,
coefs = TRUE, # muestra coeficientes
stand = TRUE, # coeficientes estandarizados
covs = FALSE, # quita covarianzas para que se vea limpio
graph_options = list(rankdir = "TB") # estructura vertical
)Parte 4: Modelo de medición
modelo4 <- '
# Recuperación (segundo orden)
desapego =~ RPD01 + RPD02 + RPD03 + RPD05 +
RPD06 + RPD07 + RPD08 + RPD09 + RPD10
relajacion =~ RRE02 + RRE03 + RRE04 + RRE05 +
RRE06 + RRE07 + RRE10
dominio =~ RMA02 + RMA03 + RMA04 + RMA05 +
RMA06 + RMA07 + RMA08 + RMA09 + RMA10
control =~ RCO02 + RCO03 + RCO04 + RCO05 +
RCO06 + RCO07
recuperacion =~ desapego + relajacion + dominio + control
# Energía
energia =~ EN01 + EN02 + EN04 + EN05 +
EN06 + EN07 + EN08
# Engagement (segundo orden)
vigor =~ EVI01 + EVI02 + EVI03
dedicacion =~ EDE01 + EDE02 + EDE03
absorcion =~ EAB01 + EAB02 + EAB03
engagement =~ vigor + dedicacion + absorcion
'
fit4 <- cfa(modelo4, df)
summary(fit4, fit.measures=TRUE, standardized=TRUE)## lavaan 0.6-21 ended normally after 74 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 104
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 2501.954
## Degrees of freedom 1024
## P-value (Chi-square) 0.000
##
## Model Test Baseline Model:
##
## Test statistic 13350.303
## Degrees of freedom 1081
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.880
## Tucker-Lewis Index (TLI) 0.873
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -15454.903
## Loglikelihood unrestricted model (H1) -14203.926
##
## Akaike (AIC) 31117.805
## Bayesian (BIC) 31472.151
## Sample-size adjusted Bayesian (SABIC) 31142.562
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.080
## 90 Percent confidence interval - lower 0.076
## 90 Percent confidence interval - upper 0.084
## P-value H_0: RMSEA <= 0.050 0.000
## P-value H_0: RMSEA >= 0.080 0.578
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.074
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## desapego =~
## RPD01 1.000 1.387 0.789
## RPD02 1.209 0.081 14.866 0.000 1.677 0.861
## RPD03 1.144 0.085 13.419 0.000 1.587 0.798
## RPD05 1.313 0.086 15.317 0.000 1.822 0.879
## RPD06 1.082 0.089 12.214 0.000 1.501 0.742
## RPD07 1.229 0.085 14.487 0.000 1.705 0.845
## RPD08 1.157 0.086 13.375 0.000 1.604 0.796
## RPD09 1.315 0.087 15.163 0.000 1.824 0.873
## RPD10 1.343 0.088 15.247 0.000 1.863 0.877
## relajacion =~
## RRE02 1.000 1.275 0.850
## RRE03 1.120 0.065 17.295 0.000 1.429 0.871
## RRE04 1.021 0.058 17.625 0.000 1.301 0.880
## RRE05 1.051 0.056 18.687 0.000 1.341 0.908
## RRE06 1.246 0.074 16.924 0.000 1.588 0.861
## RRE07 1.121 0.071 15.838 0.000 1.430 0.829
## RRE10 0.814 0.067 12.134 0.000 1.038 0.698
## dominio =~
## RMA02 1.000 1.407 0.729
## RMA03 1.152 0.096 12.041 0.000 1.621 0.798
## RMA04 1.178 0.089 13.265 0.000 1.658 0.873
## RMA05 1.141 0.087 13.057 0.000 1.605 0.860
## RMA06 0.648 0.075 8.625 0.000 0.911 0.581
## RMA07 1.104 0.085 13.062 0.000 1.553 0.861
## RMA08 1.110 0.085 13.001 0.000 1.561 0.857
## RMA09 1.030 0.084 12.257 0.000 1.448 0.811
## RMA10 1.056 0.088 12.047 0.000 1.486 0.798
## control =~
## RCO02 1.000 1.632 0.855
## RCO03 0.945 0.049 19.172 0.000 1.543 0.910
## RCO04 0.794 0.044 18.100 0.000 1.295 0.884
## RCO05 0.814 0.043 18.926 0.000 1.329 0.904
## RCO06 0.837 0.045 18.407 0.000 1.365 0.892
## RCO07 0.836 0.046 18.205 0.000 1.364 0.887
## recuperacion =~
## desapego 1.000 0.711 0.711
## relajacion 1.070 0.121 8.840 0.000 0.827 0.827
## dominio 0.900 0.129 6.960 0.000 0.631 0.631
## control 1.423 0.157 9.062 0.000 0.860 0.860
## energia =~
## EN01 1.000 1.678 0.896
## EN02 1.027 0.044 23.415 0.000 1.723 0.933
## EN04 0.998 0.044 22.871 0.000 1.675 0.925
## EN05 0.996 0.042 23.836 0.000 1.671 0.939
## EN06 0.983 0.041 23.857 0.000 1.649 0.939
## EN07 1.045 0.045 22.964 0.000 1.753 0.926
## EN08 1.033 0.042 24.398 0.000 1.733 0.946
## vigor =~
## EVI01 1.000 1.684 0.967
## EVI02 0.985 0.028 35.282 0.000 1.659 0.962
## EVI03 0.996 0.048 20.546 0.000 1.677 0.836
## dedicacion =~
## EDE01 1.000 1.868 0.952
## EDE02 0.907 0.034 26.376 0.000 1.695 0.922
## EDE03 0.571 0.037 15.539 0.000 1.066 0.754
## absorcion =~
## EAB01 1.000 1.607 0.917
## EAB02 0.711 0.051 13.823 0.000 1.143 0.752
## EAB03 0.735 0.063 11.600 0.000 1.181 0.671
## engagement =~
## vigor 1.000 0.901 0.901
## dedicacion 1.213 0.061 19.812 0.000 0.985 0.985
## absorcion 0.958 0.059 16.370 0.000 0.904 0.904
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## recuperacion ~~
## energia 1.365 0.197 6.933 0.000 0.825 0.825
## engagement 0.892 0.152 5.883 0.000 0.597 0.597
## energia ~~
## engagement 1.619 0.223 7.273 0.000 0.636 0.636
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .RPD01 1.168 0.119 9.781 0.000 1.168 0.378
## .RPD02 0.983 0.107 9.202 0.000 0.983 0.259
## .RPD03 1.434 0.147 9.729 0.000 1.434 0.363
## .RPD05 0.972 0.109 8.938 0.000 0.972 0.227
## .RPD06 1.836 0.184 9.980 0.000 1.836 0.449
## .RPD07 1.165 0.124 9.377 0.000 1.165 0.286
## .RPD08 1.486 0.153 9.740 0.000 1.486 0.366
## .RPD09 1.037 0.115 9.036 0.000 1.037 0.238
## .RPD10 1.046 0.116 8.984 0.000 1.046 0.232
## .RRE02 0.623 0.067 9.252 0.000 0.623 0.277
## .RRE03 0.647 0.072 8.976 0.000 0.647 0.241
## .RRE04 0.492 0.056 8.829 0.000 0.492 0.225
## .RRE05 0.384 0.047 8.203 0.000 0.384 0.176
## .RRE06 0.880 0.097 9.122 0.000 0.880 0.259
## .RRE07 0.930 0.098 9.460 0.000 0.930 0.313
## .RRE10 1.136 0.113 10.087 0.000 1.136 0.513
## .RMA02 1.741 0.175 9.935 0.000 1.741 0.468
## .RMA03 1.499 0.156 9.594 0.000 1.499 0.363
## .RMA04 0.857 0.098 8.785 0.000 0.857 0.238
## .RMA05 0.903 0.101 8.983 0.000 0.903 0.260
## .RMA06 1.626 0.158 10.280 0.000 1.626 0.662
## .RMA07 0.844 0.094 8.979 0.000 0.844 0.259
## .RMA08 0.882 0.098 9.031 0.000 0.882 0.266
## .RMA09 1.090 0.115 9.498 0.000 1.090 0.342
## .RMA10 1.257 0.131 9.592 0.000 1.257 0.363
## .RCO02 0.978 0.104 9.391 0.000 0.978 0.269
## .RCO03 0.493 0.058 8.474 0.000 0.493 0.172
## .RCO04 0.468 0.052 9.016 0.000 0.468 0.218
## .RCO05 0.393 0.046 8.621 0.000 0.393 0.182
## .RCO06 0.479 0.054 8.884 0.000 0.479 0.205
## .RCO07 0.505 0.056 8.972 0.000 0.505 0.213
## .EN01 0.696 0.072 9.660 0.000 0.696 0.198
## .EN02 0.443 0.049 9.064 0.000 0.443 0.130
## .EN04 0.473 0.051 9.236 0.000 0.473 0.144
## .EN05 0.378 0.042 8.907 0.000 0.378 0.119
## .EN06 0.366 0.041 8.899 0.000 0.366 0.119
## .EN07 0.507 0.055 9.209 0.000 0.507 0.142
## .EN08 0.353 0.041 8.658 0.000 0.353 0.105
## .EVI01 0.199 0.039 5.047 0.000 0.199 0.065
## .EVI02 0.224 0.040 5.620 0.000 0.224 0.075
## .EVI03 1.213 0.124 9.773 0.000 1.213 0.301
## .EDE01 0.363 0.065 5.605 0.000 0.363 0.094
## .EDE02 0.506 0.067 7.567 0.000 0.506 0.150
## .EDE03 0.864 0.087 9.921 0.000 0.864 0.432
## .EAB01 0.490 0.103 4.767 0.000 0.490 0.159
## .EAB02 1.003 0.109 9.186 0.000 1.003 0.434
## .EAB03 1.706 0.176 9.719 0.000 1.706 0.550
## .desapego 0.952 0.149 6.396 0.000 0.495 0.495
## .relajacion 0.514 0.085 6.023 0.000 0.316 0.316
## .dominio 1.191 0.200 5.956 0.000 0.602 0.602
## .control 0.694 0.125 5.538 0.000 0.261 0.261
## recuperacion 0.972 0.199 4.892 0.000 1.000 1.000
## energia 2.816 0.327 8.605 0.000 1.000 1.000
## .vigor 0.536 0.085 6.327 0.000 0.189 0.189
## .dedicacion 0.102 0.090 1.142 0.253 0.029 0.029
## .absorcion 0.472 0.112 4.233 0.000 0.183 0.183
## engagement 2.301 0.284 8.092 0.000 1.000 1.000lavaanPlot(
model = fit4,
coefs = TRUE,
stand = TRUE,
covs = FALSE,
graph_options = list(rankdir = "TB")
)