Test Dataset: 3-Factor-3-Item
data_test_3_factor_3_item.RdA dataset for testing.
Format
A data frame with 200 rows and 3 variables:
- x1
Numeric.
- x2
Numeric.
- x3
Numeric.
- m1
Numeric.
- m2
Numeric.
- m3
Numeric.
- y1
Numeric.
- y2
Numeric.
- y3
Numeric.
Examples
library(lavaan)
data(data_test_3_factor_3_item)
mod <-
"
fx =~ x1 + x2 + x3
fm =~ m1 + m2 + m3
fy =~ y1 + y2 + y3
"
fit <- sem(mod, data_test_3_factor_3_item)
parameterEstimates(fit)
#> lhs op rhs est se z pvalue ci.lower ci.upper
#> 1 fx =~ x1 1.000 0.000 NA NA 1.000 1.000
#> 2 fx =~ x2 1.081 0.237 4.570 0.000 0.617 1.545
#> 3 fx =~ x3 0.733 0.153 4.791 0.000 0.433 1.034
#> 4 fm =~ m1 1.000 0.000 NA NA 1.000 1.000
#> 5 fm =~ m2 0.519 0.112 4.637 0.000 0.300 0.739
#> 6 fm =~ m3 0.513 0.107 4.819 0.000 0.305 0.722
#> 7 fy =~ y1 1.000 0.000 NA NA 1.000 1.000
#> 8 fy =~ y2 0.512 0.116 4.398 0.000 0.284 0.740
#> 9 fy =~ y3 0.540 0.121 4.476 0.000 0.304 0.777
#> 10 x1 ~~ x1 1.192 0.187 6.361 0.000 0.825 1.559
#> 11 x2 ~~ x2 0.683 0.181 3.775 0.000 0.329 1.038
#> 12 x3 ~~ x3 1.180 0.142 8.288 0.000 0.901 1.459
#> 13 m1 ~~ m1 0.434 0.239 1.818 0.069 -0.034 0.903
#> 14 m2 ~~ m2 1.137 0.132 8.612 0.000 0.878 1.396
#> 15 m3 ~~ m3 0.848 0.106 7.978 0.000 0.640 1.056
#> 16 y1 ~~ y1 0.676 0.271 2.496 0.013 0.145 1.208
#> 17 y2 ~~ y2 1.057 0.128 8.252 0.000 0.806 1.308
#> 18 y3 ~~ y3 1.003 0.128 7.839 0.000 0.752 1.254
#> 19 fx ~~ fx 0.701 0.206 3.399 0.001 0.297 1.105
#> 20 fm ~~ fm 1.314 0.290 4.535 0.000 0.746 1.881
#> 21 fy ~~ fy 1.323 0.323 4.098 0.000 0.690 1.956
#> 22 fx ~~ fm 0.198 0.098 2.015 0.044 0.005 0.390
#> 23 fx ~~ fy -0.006 0.097 -0.065 0.949 -0.196 0.184
#> 24 fm ~~ fy 0.420 0.129 3.244 0.001 0.166 0.674