# ===============================
# PAQUETES
# ===============================
library(lavaan)
## This is lavaan 0.6-21
## lavaan is FREE software! Please report any bugs.
library(lavaanPlot)
library(cSEM)
##
## Adjuntando el paquete: 'cSEM'
## The following object is masked from 'package:lavaan':
##
## predict
## The following object is masked from 'package:stats':
##
## predict
## The following object is masked from 'package:grDevices':
##
## savePlot
# ===============================
# MODELO 1 - HOLZINGER
# ===============================
bd <- HolzingerSwineford1939
modelo <- '
visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9
'
fit <- cfa(modelo, data = bd)
summary(fit, fit.measures = TRUE, standardized = TRUE)
## lavaan 0.6-21 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
##
## Model Test Baseline Model:
##
## Test statistic 918.852
## Degrees of freedom 36
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.931
## Tucker-Lewis Index (TLI) 0.896
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -3737.745
## Loglikelihood unrestricted model (H1) -3695.092
##
## Akaike (AIC) 7517.490
## Bayesian (BIC) 7595.339
## Sample-size adjusted Bayesian (SABIC) 7528.739
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.092
## 90 Percent confidence interval - lower 0.071
## 90 Percent confidence interval - upper 0.114
## P-value H_0: RMSEA <= 0.050 0.001
## P-value H_0: RMSEA >= 0.080 0.840
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.065
##
## 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
## visual =~
## x1 1.000 0.900 0.772
## x2 0.554 0.100 5.554 0.000 0.498 0.424
## x3 0.729 0.109 6.685 0.000 0.656 0.581
## textual =~
## x4 1.000 0.990 0.852
## x5 1.113 0.065 17.014 0.000 1.102 0.855
## x6 0.926 0.055 16.703 0.000 0.917 0.838
## speed =~
## x7 1.000 0.619 0.570
## x8 1.180 0.165 7.152 0.000 0.731 0.723
## x9 1.082 0.151 7.155 0.000 0.670 0.665
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## visual ~~
## textual 0.408 0.074 5.552 0.000 0.459 0.459
## speed 0.262 0.056 4.660 0.000 0.471 0.471
## textual ~~
## speed 0.173 0.049 3.518 0.000 0.283 0.283
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .x1 0.549 0.114 4.833 0.000 0.549 0.404
## .x2 1.134 0.102 11.146 0.000 1.134 0.821
## .x3 0.844 0.091 9.317 0.000 0.844 0.662
## .x4 0.371 0.048 7.779 0.000 0.371 0.275
## .x5 0.446 0.058 7.642 0.000 0.446 0.269
## .x6 0.356 0.043 8.277 0.000 0.356 0.298
## .x7 0.799 0.081 9.823 0.000 0.799 0.676
## .x8 0.488 0.074 6.573 0.000 0.488 0.477
## .x9 0.566 0.071 8.003 0.000 0.566 0.558
## visual 0.809 0.145 5.564 0.000 1.000 1.000
## textual 0.979 0.112 8.737 0.000 1.000 1.000
## speed 0.384 0.086 4.451 0.000 1.000 1.000
lavaanPlot(model = fit, coefs = TRUE, covs = TRUE)
# ===============================
# MODELO 2 - PoliticalDemocracy (CFA)
# ===============================
data("PoliticalDemocracy")
bd2 <- PoliticalDemocracy
modelo2 <- '
democracy_1960 =~ y1 + y2 + y3 + y4
democracy_1965 =~ y5 + y6 + y7 + y8
industrialization_1960 =~ x1 + x2 + x3
'
fit2 <- cfa(modelo2, data = bd2)
summary(fit2, fit.measures = TRUE, standardized = TRUE)
## lavaan 0.6-21 ended normally after 47 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 25
##
## Number of observations 75
##
## Model Test User Model:
##
## Test statistic 72.462
## Degrees of freedom 41
## P-value (Chi-square) 0.002
##
## Model Test Baseline Model:
##
## Test statistic 730.654
## Degrees of freedom 55
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.953
## Tucker-Lewis Index (TLI) 0.938
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1564.959
## Loglikelihood unrestricted model (H1) -1528.728
##
## Akaike (AIC) 3179.918
## Bayesian (BIC) 3237.855
## Sample-size adjusted Bayesian (SABIC) 3159.062
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.101
## 90 Percent confidence interval - lower 0.061
## 90 Percent confidence interval - upper 0.139
## P-value H_0: RMSEA <= 0.050 0.021
## P-value H_0: RMSEA >= 0.080 0.827
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.055
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## democracy_1960 =~
## y1 1.000 2.201
## y2 1.354 0.175 7.755 0.000 2.980
## y3 1.044 0.150 6.961 0.000 2.298
## y4 1.300 0.138 9.412 0.000 2.860
## democracy_1965 =~
## y5 1.000 2.084
## y6 1.258 0.164 7.651 0.000 2.623
## y7 1.282 0.158 8.137 0.000 2.673
## y8 1.310 0.154 8.529 0.000 2.730
## industrialization_1960 =~
## x1 1.000 0.669
## x2 2.182 0.139 15.714 0.000 1.461
## x3 1.819 0.152 11.956 0.000 1.218
## Std.all
##
## 0.845
## 0.760
## 0.705
## 0.860
##
## 0.803
## 0.783
## 0.819
## 0.847
##
## 0.920
## 0.973
## 0.872
##
## Covariances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## democracy_1960 ~~
## democracy_1965 4.487 0.911 4.924 0.000 0.978 0.978
## indstrlzt_1960 0.660 0.206 3.202 0.001 0.448 0.448
## democracy_1965 ~~
## indstrlzt_1960 0.774 0.208 3.715 0.000 0.555 0.555
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .y1 1.942 0.395 4.910 0.000 1.942 0.286
## .y2 6.490 1.185 5.479 0.000 6.490 0.422
## .y3 5.340 0.943 5.662 0.000 5.340 0.503
## .y4 2.887 0.610 4.731 0.000 2.887 0.261
## .y5 2.390 0.447 5.351 0.000 2.390 0.355
## .y6 4.343 0.796 5.456 0.000 4.343 0.387
## .y7 3.510 0.668 5.252 0.000 3.510 0.329
## .y8 2.940 0.586 5.019 0.000 2.940 0.283
## .x1 0.082 0.020 4.180 0.000 0.082 0.154
## .x2 0.118 0.070 1.689 0.091 0.118 0.053
## .x3 0.467 0.090 5.174 0.000 0.467 0.240
## democracy_1960 4.845 1.088 4.453 0.000 1.000 1.000
## democracy_1965 4.345 1.051 4.134 0.000 1.000 1.000
## indstrlzt_1960 0.448 0.087 5.169 0.000 1.000 1.000
lavaanPlot(model = fit2, coefs = TRUE, covs = TRUE)
# ===============================
# MODELO 3 - SEM (REGRESIÓN ESTRUCTURAL)
# ===============================
modelo_sem <- '
democracy_1960 =~ y1 + y2 + y3 + y4
democracy_1965 =~ y5 + y6 + y7 + y8
industrialization_1960 =~ x1 + x2 + x3
democracy_1960 ~ industrialization_1960
democracy_1965 ~ democracy_1960 + industrialization_1960
'
fit_sem <- sem(modelo_sem, data = bd2)
summary(fit_sem, fit.measures = TRUE, standardized = TRUE)
## lavaan 0.6-21 ended normally after 42 iterations
##
## Estimator ML
## Optimization method NLMINB
## Number of model parameters 25
##
## Number of observations 75
##
## Model Test User Model:
##
## Test statistic 72.462
## Degrees of freedom 41
## P-value (Chi-square) 0.002
##
## Model Test Baseline Model:
##
## Test statistic 730.654
## Degrees of freedom 55
## P-value 0.000
##
## User Model versus Baseline Model:
##
## Comparative Fit Index (CFI) 0.953
## Tucker-Lewis Index (TLI) 0.938
##
## Loglikelihood and Information Criteria:
##
## Loglikelihood user model (H0) -1564.959
## Loglikelihood unrestricted model (H1) -1528.728
##
## Akaike (AIC) 3179.918
## Bayesian (BIC) 3237.855
## Sample-size adjusted Bayesian (SABIC) 3159.062
##
## Root Mean Square Error of Approximation:
##
## RMSEA 0.101
## 90 Percent confidence interval - lower 0.061
## 90 Percent confidence interval - upper 0.139
## P-value H_0: RMSEA <= 0.050 0.021
## P-value H_0: RMSEA >= 0.080 0.827
##
## Standardized Root Mean Square Residual:
##
## SRMR 0.055
##
## Parameter Estimates:
##
## Standard errors Standard
## Information Expected
## Information saturated (h1) model Structured
##
## Latent Variables:
## Estimate Std.Err z-value P(>|z|) Std.lv
## democracy_1960 =~
## y1 1.000 2.201
## y2 1.354 0.175 7.755 0.000 2.980
## y3 1.044 0.150 6.961 0.000 2.298
## y4 1.300 0.138 9.412 0.000 2.860
## democracy_1965 =~
## y5 1.000 2.084
## y6 1.258 0.164 7.651 0.000 2.623
## y7 1.282 0.158 8.137 0.000 2.673
## y8 1.310 0.154 8.529 0.000 2.730
## industrialization_1960 =~
## x1 1.000 0.669
## x2 2.182 0.139 15.714 0.000 1.461
## x3 1.819 0.152 11.956 0.000 1.218
## Std.all
##
## 0.845
## 0.760
## 0.705
## 0.860
##
## 0.803
## 0.783
## 0.819
## 0.847
##
## 0.920
## 0.973
## 0.872
##
## Regressions:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## democracy_1960 ~
## indstrlzt_1960 1.474 0.392 3.763 0.000 0.448 0.448
## democracy_1965 ~
## democracy_1960 0.864 0.113 7.671 0.000 0.913 0.913
## indstrlzt_1960 0.453 0.220 2.064 0.039 0.146 0.146
##
## Variances:
## Estimate Std.Err z-value P(>|z|) Std.lv Std.all
## .y1 1.942 0.395 4.910 0.000 1.942 0.286
## .y2 6.490 1.185 5.479 0.000 6.490 0.422
## .y3 5.340 0.943 5.662 0.000 5.340 0.503
## .y4 2.887 0.610 4.731 0.000 2.887 0.261
## .y5 2.390 0.447 5.351 0.000 2.390 0.355
## .y6 4.343 0.796 5.456 0.000 4.343 0.387
## .y7 3.510 0.668 5.252 0.000 3.510 0.329
## .y8 2.940 0.586 5.019 0.000 2.940 0.283
## .x1 0.082 0.020 4.180 0.000 0.082 0.154
## .x2 0.118 0.070 1.689 0.091 0.118 0.053
## .x3 0.467 0.090 5.174 0.000 0.467 0.240
## .democracy_1960 3.872 0.893 4.338 0.000 0.799 0.799
## .democracy_1965 0.115 0.200 0.575 0.565 0.026 0.026
## indstrlzt_1960 0.448 0.087 5.169 0.000 1.000 1.000
lavaanPlot(model = fit_sem, coefs = TRUE, covs = TRUE)