estimate_mx(x, ...)An object of class MxModel.
df <- iris[1:4]
names(df) <- paste0("x_", 1:4)
model <- tidy_sem(df)
model <- measurement(model)
res <- estimate_mx(model)
#> Running model with 12 parameters
summary(res)
#> Summary of model
#>
#> free parameters:
#> name matrix row col Estimate Std.Error A
#> 1 model.A[2,5] A x_2 x -0.3496930 0.04368339
#> 2 model.A[3,5] A x_3 x 2.7756478 0.16956099
#> 3 model.A[4,5] A x_4 x 1.0270097 0.06929740
#> 4 model.S[1,1] S x_1 x_1 0.2352754 0.02950895
#> 5 model.S[2,2] S x_2 x_2 0.1341924 0.01400658
#> 6 model.S[3,3] S x_3 x_3 -0.3393999 0.08105053
#> 7 model.S[4,4] S x_4 x_4 0.1068763 0.01823782
#> 8 model.S[5,5] S x x 0.4458469 0.07470965
#> 9 model.M[1,1] M 1 x_1 5.8433333 0.06738552
#> 10 model.M[1,2] M 1 x_2 3.0573333 0.03546949
#> 11 model.M[1,3] M 1 x_3 3.7580000 0.14365460
#> 12 model.M[1,4] M 1 x_4 1.1993333 0.06202858
#>
#> Model Statistics:
#> | Parameters | Degrees of Freedom | Fit (-2lnL units)
#> Model: 12 588 819.4226
#> Saturated: 14 586 NA
#> Independence: 8 592 NA
#> Number of observations/statistics: 150/600
#>
#> Information Criteria:
#> | df Penalty | Parameters Penalty | Sample-Size Adjusted
#> AIC: -356.5774 843.4226 845.7000
#> BIC: -2126.8309 879.5503 841.5725
#> To get additional fit indices, see help(mxRefModels)
#> timestamp: 2025-01-16 13:41:19
#> Wall clock time: 0.03960299 secs
#> optimizer: SLSQP
#> OpenMx version number: 2.21.13
#> Need help? See help(mxSummary)
#>