Actividad 3. Aplicación de modelos de ecuaciones estructurales
Los ejercicios de esta actividad realizados en equipo fueron elaborados por Astrid Paola González Diaz, José Santiago González Padilla, y Ana Estefanía López Alanís.
Ejemplo “Estudio de Holzinger y Swineford (1939)”
Contexto
Los Modelos de Ecuaciones Estructurales (SEM) son una técnica de análisis de estadística multivariante que permite analizar patrones complejos de relaciones entre variables, realizar comparaciones entre intragrupos, y validar modelos teóricos y empíricos.
Holzinger y Swineford realizaron exámenes de habilidad mental a adolescentes de 7mo y 8vo grado de dos escuelas (Pasteur y Grand-White).
La base de datos está incluida como paquete en R, e incluye las siguientes columnas:
- id: Identificador
- sex: Género (1 = male, 2 = female)
- ageyr: Edad (11 a 16)
- x1: Percepción visual
- x2: Juego con cubos
- x3: Juego con pastillas
- x4: Comprensión de párrafos
- x5: Completar oraciones
- x6: Significados de palabras
- x7: Sumas aceleradas
- x8: Conteo acelerado de puntos
- x9: Discriminación acelerada de mayúsculas rectas y curvas
Se busca identificar las relaciones entre habilidades visuales (x1, x2, x3), textuales (x4, x5, x6) y velocidad de razonamiento (x7, x8, x9).
Tipos de fórmulas
- Regresión (~) Variable que depende de otras.
- Variables latentes (=~) No se observan, se infieren.
- Análisis de varianzas y covarianzas (~~) Relaciones entre variables latentes y observadas. (Varianza es entre si misma, covarianza entre otras)
- Intercepto (~1) Valor esperado cuando las demás variables son cero.
Estructura del modelo
Análisis Factorial Confirmatorio (CFA)
## lavaan 0.6.17 ended normally after 35 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 21
##
## Number of observations 301
##
## Model Test User Model:
##
## Test statistic 85.306
## 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|)
## visual =~
## x1 1.000
## x2 0.554 0.100 5.554 0.000
## x3 0.729 0.109 6.685 0.000
## textual =~
## x4 1.000
## x5 1.113 0.065 17.014 0.000
## x6 0.926 0.055 16.703 0.000
## velocidad =~
## x7 1.000
## x8 1.180 0.165 7.152 0.000
## x9 1.082 0.151 7.155 0.000
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## visual ~~
## textual 0.408 0.074 5.552 0.000
## velocidad 0.262 0.056 4.660 0.000
## textual ~~
## velocidad 0.173 0.049 3.518 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .x1 0.549 0.114 4.833 0.000
## .x2 1.134 0.102 11.146 0.000
## .x3 0.844 0.091 9.317 0.000
## .x4 0.371 0.048 7.779 0.000
## .x5 0.446 0.058 7.642 0.000
## .x6 0.356 0.043 8.277 0.000
## .x7 0.799 0.081 9.823 0.000
## .x8 0.488 0.074 6.573 0.000
## .x9 0.566 0.071 8.003 0.000
## visual 0.809 0.145 5.564 0.000
## textual 0.979 0.112 8.737 0.000
## velocidad 0.384 0.086 4.451 0.000Ejercicio “Democracia Política e Industrialización”
Contexto
La base de datos contiene distintas mediciones sobre la democracia política e industrialización en países en desarrollo durante 1960 y 1965.
La tabla incluye los siguientes datos:
- y1: Calificaciones sobre la libertad de prensa.
- y2: Libertad de la oposición política en 1960.
- y3: Imparcialidad de elecciones en 1960.
- y4: Eficacia de la legislatura electa en 1960.
- y5: Calificaciones sobre la libertad de prensa en 1965.
- y6: Libertad de la oposición política en 1965.
- y7: Imparcialidad de elecciones en 1965.
- y8: Eficacia de la legislatura electa en 1965.
- x1: PIB per Capita 1960.
- x2: Consumo de energía inanimada.
- x3: Porcentaje de la fuerza laboral en la industria en 1960.
Se busca identificar las relaciones entre la democracia en 1960 (y1, y2, y3, y4), democracia en 1965 (y5, y6, y7, y8) y la industrialización (x1, x2, x3).
Estructura del modelo
Análisis Factorial Confirmatorio (CFA)
## lavaan 0.6.17 ended normally after 51 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 27
##
## Number of observations 75
##
## Model Test User Model:
##
## Test statistic 70.505
## Degrees of freedom 39
## P-value (Chi-square) 0.001
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|)
## democracia60 =~
## y1 1.000
## y2 1.346 0.172 7.813 0.000
## y3 1.023 0.148 6.920 0.000
## y4 1.280 0.136 9.436 0.000
## democracia65 =~
## y5 1.000
## y6 1.289 0.167 7.735 0.000
## y7 1.289 0.161 8.010 0.000
## y8 1.717 0.343 5.012 0.000
## industrializacion60 =~
## x1 1.000
## x2 2.182 0.139 15.701 0.000
## x3 1.819 0.152 11.949 0.000
##
## Regressions:
## Estimate Std.Err z-value P(>|z|)
## y8 ~
## y1 -0.247 0.192 -1.288 0.198
## y2 -0.074 0.094 -0.779 0.436
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## democracia60 ~~
## democracia65 4.513 0.915 4.931 0.000
## industrilzcn60 0.663 0.208 3.193 0.001
## democracia65 ~~
## industrilzcn60 0.735 0.203 3.614 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .y1 1.856 0.390 4.755 0.000
## .y2 6.445 1.189 5.419 0.000
## .y3 5.458 0.953 5.728 0.000
## .y4 2.989 0.618 4.837 0.000
## .y5 2.483 0.452 5.495 0.000
## .y6 4.161 0.756 5.501 0.000
## .y7 3.593 0.666 5.393 0.000
## .y8 2.477 0.633 3.916 0.000
## .x1 0.082 0.020 4.174 0.000
## .x2 0.118 0.070 1.673 0.094
## .x3 0.468 0.090 5.173 0.000
## democracia60 4.931 1.094 4.507 0.000
## democracia65 4.251 1.042 4.082 0.000
## industrilzcn60 0.448 0.087 5.168 0.000Actividad “Bienestar de los Colaboradores”
Contexto
Uno de los retos más importantes de las organizaciones es entender el estado y bienestar de los colaboradores, ya que puede impactar directamente en el desempeño y el logro de los objetivos.
Importar y entender la base de datos
Parte 1. Experiencias de Recuperación
Estructura del modelo y análisis factorial confirmatorio
modelo3 <- ' # Regresiones
# 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
recuperacion =~ desapego + relajacion + dominio + control
# Varianzas y Covarianzas
# Intercepto
'
fit3 <- cfa(modelo3, df3)
summary(fit3)## lavaan 0.6.17 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
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|)
## desapego =~
## RPD01 1.000
## RPD02 1.206 0.082 14.780 0.000
## RPD03 1.143 0.085 13.374 0.000
## RPD05 1.312 0.086 15.244 0.000
## RPD06 1.088 0.089 12.266 0.000
## RPD07 1.229 0.085 14.440 0.000
## RPD08 1.164 0.087 13.447 0.000
## RPD09 1.317 0.087 15.153 0.000
## RPD10 1.346 0.088 15.258 0.000
## relajacion =~
## RRE02 1.000
## RRE03 1.120 0.065 17.227 0.000
## RRE04 1.025 0.058 17.713 0.000
## RRE05 1.055 0.056 18.758 0.000
## RRE06 1.245 0.074 16.869 0.000
## RRE07 1.117 0.071 15.689 0.000
## RRE10 0.815 0.067 12.120 0.000
## dominio =~
## RMA02 1.000
## RMA03 1.155 0.096 12.079 0.000
## RMA04 1.178 0.089 13.274 0.000
## RMA05 1.141 0.087 13.072 0.000
## RMA06 0.645 0.075 8.597 0.000
## RMA07 1.103 0.084 13.061 0.000
## RMA08 1.109 0.085 12.994 0.000
## RMA09 1.028 0.084 12.246 0.000
## RMA10 1.055 0.088 12.044 0.000
## control =~
## RCO02 1.000
## RCO03 0.948 0.049 19.182 0.000
## RCO04 0.796 0.044 18.110 0.000
## RCO05 0.818 0.043 18.990 0.000
## RCO06 0.834 0.046 18.216 0.000
## RCO07 0.835 0.046 18.057 0.000
## recuperacion =~
## desapego 1.000
## relajacion 1.149 0.131 8.787 0.000
## dominio 0.858 0.129 6.666 0.000
## control 1.341 0.156 8.605 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .RPD01 1.172 0.120 9.782 0.000
## .RPD02 0.999 0.108 9.228 0.000
## .RPD03 1.441 0.148 9.733 0.000
## .RPD05 0.987 0.110 8.964 0.000
## .RPD06 1.817 0.182 9.967 0.000
## .RPD07 1.173 0.125 9.383 0.000
## .RPD08 1.460 0.150 9.714 0.000
## .RPD09 1.032 0.114 9.021 0.000
## .RPD10 1.034 0.115 8.955 0.000
## .RRE02 0.626 0.068 9.274 0.000
## .RRE03 0.653 0.073 9.011 0.000
## .RRE04 0.481 0.055 8.794 0.000
## .RRE05 0.374 0.046 8.153 0.000
## .RRE06 0.886 0.097 9.149 0.000
## .RRE07 0.950 0.100 9.505 0.000
## .RRE10 1.137 0.113 10.093 0.000
## .RMA02 1.740 0.175 9.931 0.000
## .RMA03 1.485 0.155 9.575 0.000
## .RMA04 0.855 0.097 8.772 0.000
## .RMA05 0.899 0.100 8.967 0.000
## .RMA06 1.631 0.159 10.281 0.000
## .RMA07 0.845 0.094 8.977 0.000
## .RMA08 0.886 0.098 9.034 0.000
## .RMA09 1.094 0.115 9.500 0.000
## .RMA10 1.259 0.131 9.590 0.000
## .RCO02 0.983 0.105 9.379 0.000
## .RCO03 0.484 0.058 8.391 0.000
## .RCO04 0.462 0.052 8.963 0.000
## .RCO05 0.382 0.045 8.513 0.000
## .RCO06 0.494 0.055 8.917 0.000
## .RCO07 0.515 0.057 8.985 0.000
## .desapego 0.943 0.152 6.207 0.000
## .relajacion 0.333 0.089 3.757 0.000
## .dominio 1.260 0.212 5.942 0.000
## .control 0.900 0.159 5.666 0.000
## recuperacion 0.978 0.202 4.833 0.000Estructura del modelo y análisis factorial confirmatorio depurado
modelo4 <- ' # Regresiones
# Variables Latentes
desapego =~ RPD01 + RPD02 + RPD03 + RPD05 + RPD07 + RPD08 + RPD09 + RPD10
relajacion =~ RRE02 + RRE03 + RRE04 + RRE05 + RRE06 + RRE07
dominio =~ RMA02 + RMA03 + RMA04 + RMA05 + RMA07 + RMA08 + RMA09 + RMA10
control =~ RCO02 + RCO03 + RCO05 + RCO06 + RCO07
recuperacion =~ desapego + relajacion + dominio + control
# Varianzas y Covarianzas
# Intercepto
'
fit4 <- cfa(modelo4, df3)
summary(fit4)## lavaan 0.6.17 ended normally after 48 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 58
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 886.791
## Degrees of freedom 320
## 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|)
## desapego =~
## RPD01 1.000
## RPD02 1.204 0.079 15.158 0.000
## RPD03 1.146 0.083 13.750 0.000
## RPD05 1.310 0.084 15.663 0.000
## RPD07 1.219 0.083 14.675 0.000
## RPD08 1.114 0.086 13.004 0.000
## RPD09 1.301 0.085 15.315 0.000
## RPD10 1.328 0.086 15.404 0.000
## relajacion =~
## RRE02 1.000
## RRE03 1.111 0.064 17.245 0.000
## RRE04 1.025 0.057 17.974 0.000
## RRE05 1.054 0.055 19.046 0.000
## RRE06 1.237 0.073 16.904 0.000
## RRE07 1.105 0.071 15.618 0.000
## dominio =~
## RMA02 1.000
## RMA03 1.155 0.095 12.223 0.000
## RMA04 1.176 0.088 13.412 0.000
## RMA05 1.140 0.086 13.220 0.000
## RMA07 1.091 0.083 13.067 0.000
## RMA08 1.103 0.084 13.087 0.000
## RMA09 1.020 0.083 12.287 0.000
## RMA10 1.049 0.087 12.097 0.000
## control =~
## RCO02 1.000
## RCO03 0.944 0.051 18.648 0.000
## RCO05 0.820 0.044 18.683 0.000
## RCO06 0.840 0.046 18.083 0.000
## RCO07 0.842 0.047 18.010 0.000
## recuperacion =~
## desapego 1.000
## relajacion 1.145 0.132 8.696 0.000
## dominio 0.843 0.129 6.525 0.000
## control 1.356 0.159 8.549 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .RPD01 1.134 0.117 9.697 0.000
## .RPD02 0.956 0.105 9.070 0.000
## .RPD03 1.381 0.143 9.629 0.000
## .RPD05 0.932 0.107 8.749 0.000
## .RPD07 1.162 0.125 9.304 0.000
## .RPD08 1.629 0.166 9.815 0.000
## .RPD09 1.053 0.117 8.980 0.000
## .RPD10 1.061 0.119 8.926 0.000
## .RRE02 0.612 0.067 9.179 0.000
## .RRE03 0.666 0.074 8.988 0.000
## .RRE04 0.467 0.054 8.651 0.000
## .RRE05 0.361 0.045 7.940 0.000
## .RRE06 0.898 0.098 9.119 0.000
## .RRE07 0.974 0.102 9.502 0.000
## .RMA02 1.720 0.174 9.901 0.000
## .RMA03 1.456 0.153 9.519 0.000
## .RMA04 0.839 0.097 8.681 0.000
## .RMA05 0.879 0.099 8.876 0.000
## .RMA07 0.874 0.097 9.009 0.000
## .RMA08 0.884 0.098 8.993 0.000
## .RMA09 1.105 0.116 9.490 0.000
## .RMA10 1.265 0.132 9.573 0.000
## .RCO02 0.999 0.109 9.187 0.000
## .RCO03 0.517 0.063 8.171 0.000
## .RCO05 0.385 0.047 8.145 0.000
## .RCO06 0.482 0.056 8.540 0.000
## .RCO07 0.495 0.058 8.582 0.000
## .desapego 0.985 0.157 6.286 0.000
## .relajacion 0.360 0.092 3.917 0.000
## .dominio 1.309 0.218 5.994 0.000
## .control 0.850 0.159 5.341 0.000
## recuperacion 0.974 0.203 4.795 0.000Parte 2. Energía Recuperada
Estructura del modelo
Análisis Factorial Confirmatorio
## lavaan 0.6.17 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
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|)
## energia =~
## EN01 1.000
## EN02 1.029 0.044 23.192 0.000
## EN04 0.999 0.044 22.583 0.000
## EN05 0.999 0.042 23.649 0.000
## EN06 0.986 0.042 23.722 0.000
## EN07 1.049 0.046 22.856 0.000
## EN08 1.036 0.043 24.173 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .EN01 0.711 0.074 9.651 0.000
## .EN02 0.444 0.049 9.012 0.000
## .EN04 0.481 0.052 9.214 0.000
## .EN05 0.375 0.042 8.830 0.000
## .EN06 0.359 0.041 8.798 0.000
## .EN07 0.499 0.055 9.129 0.000
## .EN08 0.353 0.041 8.580 0.000
## energia 2.801 0.327 8.565 0.000Después de evaluar los valores estimativos, los errores estándar y el p-value, determinamos innecesario depurar el modelo.
Parte 3. Engagement Laboral
Estructura del modelo
modelo6 <- ' # Regresiones
# Variables Latentes 1
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
# Variables Latentes 2
energia =~ EN01 + EN02 + EN04 + EN05 + EN06 + EN07 + EN08
# Variables Latentes 3
vigor =~ EVI01 + EVI02 + EVI03
dedicacion =~ EDE01 + EDE02 + EDE03
absorcion =~ EAB01 + EAB02
engagement =~ vigor + dedicacion + absorcion
# Varianzas y Covarianzas
engagement ~~ energia + recuperacion
# Intercepto
'Análisis de Senderos
## lavaan 0.6.17 ended normally after 73 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 102
##
## Number of observations 223
##
## Model Test User Model:
##
## Test statistic 2395.225
## Degrees of freedom 979
## 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|)
## desapego =~
## RPD01 1.000
## RPD02 1.209 0.081 14.866 0.000
## RPD03 1.144 0.085 13.419 0.000
## RPD05 1.313 0.086 15.317 0.000
## RPD06 1.082 0.089 12.214 0.000
## RPD07 1.229 0.085 14.487 0.000
## RPD08 1.157 0.086 13.375 0.000
## RPD09 1.315 0.087 15.163 0.000
## RPD10 1.343 0.088 15.247 0.000
## relajacion =~
## RRE02 1.000
## RRE03 1.120 0.065 17.295 0.000
## RRE04 1.021 0.058 17.626 0.000
## RRE05 1.051 0.056 18.687 0.000
## RRE06 1.246 0.074 16.924 0.000
## RRE07 1.121 0.071 15.837 0.000
## RRE10 0.814 0.067 12.134 0.000
## dominio =~
## RMA02 1.000
## RMA03 1.152 0.096 12.041 0.000
## RMA04 1.178 0.089 13.265 0.000
## RMA05 1.141 0.087 13.057 0.000
## RMA06 0.648 0.075 8.625 0.000
## RMA07 1.104 0.085 13.062 0.000
## RMA08 1.110 0.085 13.001 0.000
## RMA09 1.030 0.084 12.257 0.000
## RMA10 1.056 0.088 12.047 0.000
## control =~
## RCO02 1.000
## RCO03 0.945 0.049 19.172 0.000
## RCO04 0.794 0.044 18.100 0.000
## RCO05 0.814 0.043 18.926 0.000
## RCO06 0.837 0.045 18.409 0.000
## RCO07 0.836 0.046 18.206 0.000
## recuperacion =~
## desapego 1.000
## relajacion 1.070 0.121 8.838 0.000
## dominio 0.900 0.129 6.959 0.000
## control 1.424 0.157 9.063 0.000
## energia =~
## EN01 1.000
## EN02 1.027 0.044 23.416 0.000
## EN04 0.998 0.044 22.870 0.000
## EN05 0.996 0.042 23.836 0.000
## EN06 0.983 0.041 23.857 0.000
## EN07 1.045 0.045 22.964 0.000
## EN08 1.033 0.042 24.399 0.000
## vigor =~
## EVI01 1.000
## EVI02 0.985 0.028 35.255 0.000
## EVI03 0.996 0.048 20.570 0.000
## dedicacion =~
## EDE01 1.000
## EDE02 0.905 0.034 26.515 0.000
## EDE03 0.567 0.037 15.447 0.000
## absorcion =~
## EAB01 1.000
## EAB02 0.656 0.053 12.368 0.000
## engagement =~
## vigor 1.000
## dedicacion 1.216 0.061 20.023 0.000
## absorcion 0.984 0.057 17.202 0.000
##
## Covariances:
## Estimate Std.Err z-value P(>|z|)
## energia ~~
## engagement 1.616 0.222 7.269 0.000
## recuperacion ~~
## engagement 0.893 0.152 5.888 0.000
## energia 1.365 0.197 6.933 0.000
##
## Variances:
## Estimate Std.Err z-value P(>|z|)
## .RPD01 1.168 0.119 9.781 0.000
## .RPD02 0.982 0.107 9.202 0.000
## .RPD03 1.434 0.147 9.729 0.000
## .RPD05 0.972 0.109 8.938 0.000
## .RPD06 1.837 0.184 9.980 0.000
## .RPD07 1.165 0.124 9.377 0.000
## .RPD08 1.486 0.153 9.740 0.000
## .RPD09 1.037 0.115 9.036 0.000
## .RPD10 1.046 0.116 8.984 0.000
## .RRE02 0.623 0.067 9.252 0.000
## .RRE03 0.647 0.072 8.976 0.000
## .RRE04 0.492 0.056 8.829 0.000
## .RRE05 0.384 0.047 8.202 0.000
## .RRE06 0.880 0.097 9.122 0.000
## .RRE07 0.930 0.098 9.460 0.000
## .RRE10 1.136 0.113 10.087 0.000
## .RMA02 1.741 0.175 9.935 0.000
## .RMA03 1.499 0.156 9.594 0.000
## .RMA04 0.857 0.098 8.785 0.000
## .RMA05 0.903 0.101 8.983 0.000
## .RMA06 1.626 0.158 10.280 0.000
## .RMA07 0.844 0.094 8.979 0.000
## .RMA08 0.882 0.098 9.031 0.000
## .RMA09 1.090 0.115 9.498 0.000
## .RMA10 1.257 0.131 9.592 0.000
## .RCO02 0.977 0.104 9.391 0.000
## .RCO03 0.493 0.058 8.475 0.000
## .RCO04 0.468 0.052 9.017 0.000
## .RCO05 0.393 0.046 8.621 0.000
## .RCO06 0.479 0.054 8.883 0.000
## .RCO07 0.505 0.056 8.972 0.000
## .EN01 0.696 0.072 9.660 0.000
## .EN02 0.443 0.049 9.063 0.000
## .EN04 0.473 0.051 9.236 0.000
## .EN05 0.378 0.042 8.907 0.000
## .EN06 0.366 0.041 8.899 0.000
## .EN07 0.507 0.055 9.209 0.000
## .EN08 0.353 0.041 8.658 0.000
## .EVI01 0.199 0.039 5.056 0.000
## .EVI02 0.224 0.040 5.637 0.000
## .EVI03 1.211 0.124 9.770 0.000
## .EDE01 0.352 0.064 5.529 0.000
## .EDE02 0.509 0.067 7.646 0.000
## .EDE03 0.874 0.088 9.945 0.000
## .EAB01 0.379 0.128 2.953 0.003
## .EAB02 1.149 0.121 9.491 0.000
## .desapego 0.953 0.149 6.397 0.000
## .relajacion 0.514 0.085 6.027 0.000
## .dominio 1.191 0.200 5.956 0.000
## .control 0.693 0.125 5.534 0.000
## recuperacion 0.972 0.199 4.892 0.000
## energia 2.816 0.327 8.605 0.000
## .vigor 0.536 0.084 6.413 0.000
## .dedicacion 0.099 0.087 1.131 0.258
## .absorcion 0.469 0.138 3.392 0.001
## engagement 2.300 0.284 8.099 0.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