A 16-variable dataset with 336 cases.
Format
A data frame with 336 rows and 16 variables:
- x1
Indicator. Numeric.
- x2
Indicator. Numeric.
- x3
Indicator. Numeric.
- x4
Indicator. Numeric.
- x5
Indicator. Numeric.
- x6
Indicator. Numeric.
- x7
Indicator. Numeric.
- x8
Indicator. Numeric.
- x9
Indicator. Numeric.
- x10
Indicator. Numeric.
- x11
Indicator. Numeric.
- x12
Indicator. Numeric.
- x13
Indicator. Numeric.
- x14
Indicator. Numeric.
- x15
Indicator. Numeric.
- x16
Indicator. Numeric.
- group
Group with two values, "alpha" and "gamma". Character.
Examples
library(lavaan)
#> This is lavaan 0.6-18
#> lavaan is FREE software! Please report any bugs.
data(data_sem16)
mod <-
"
f1 =~ x1 + x2 + x3 + x4
f2 =~ x5 + x6 + x7 + x8
f3 =~ x9 + x10 + x11 + x12
f4 =~ x13 + x14 + x15 + x16
f3 ~ f2 + f1
f4 ~ f3
"
fit <- sem(mod, data_sem16)
summary(fit)
#> lavaan 0.6-18 ended normally after 53 iterations
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 36
#>
#> Number of observations 336
#>
#> Model Test User Model:
#>
#> Test statistic 86.336
#> Degrees of freedom 100
#> P-value (Chi-square) 0.833
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Latent Variables:
#> Estimate Std.Err z-value P(>|z|)
#> f1 =~
#> x1 1.000
#> x2 0.888 0.200 4.446 0.000
#> x3 1.049 0.216 4.863 0.000
#> x4 0.582 0.168 3.470 0.001
#> f2 =~
#> x5 1.000
#> x6 1.202 0.328 3.667 0.000
#> x7 0.792 0.240 3.294 0.001
#> x8 0.407 0.188 2.168 0.030
#> f3 =~
#> x9 1.000
#> x10 0.854 0.135 6.343 0.000
#> x11 0.920 0.139 6.634 0.000
#> x12 0.814 0.133 6.114 0.000
#> f4 =~
#> x13 1.000
#> x14 1.077 0.215 5.008 0.000
#> x15 0.475 0.143 3.319 0.001
#> x16 0.939 0.193 4.857 0.000
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|)
#> f3 ~
#> f2 0.455 0.208 2.185 0.029
#> f1 0.555 0.174 3.195 0.001
#> f4 ~
#> f3 0.561 0.115 4.887 0.000
#>
#> Covariances:
#> Estimate Std.Err z-value P(>|z|)
#> f1 ~~
#> f2 0.109 0.038 2.864 0.004
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|)
#> .x1 0.999 0.099 10.059 0.000
#> .x2 1.070 0.099 10.849 0.000
#> .x3 0.689 0.083 8.334 0.000
#> .x4 1.120 0.092 12.110 0.000
#> .x5 0.965 0.098 9.832 0.000
#> .x6 0.888 0.110 8.055 0.000
#> .x7 1.037 0.093 11.178 0.000
#> .x8 1.006 0.081 12.487 0.000
#> .x9 0.961 0.097 9.862 0.000
#> .x10 1.010 0.093 10.817 0.000
#> .x11 0.941 0.091 10.283 0.000
#> .x12 1.069 0.096 11.128 0.000
#> .x13 1.107 0.111 10.006 0.000
#> .x14 1.113 0.117 9.541 0.000
#> .x15 1.073 0.087 12.292 0.000
#> .x16 1.064 0.104 10.255 0.000
#> f1 0.297 0.089 3.322 0.001
#> f2 0.217 0.083 2.617 0.009
#> .f3 0.300 0.077 3.881 0.000
#> .f4 0.200 0.070 2.866 0.004
#>