| Models Info | ||
|---|---|---|
| Estimation Method | ML | . |
| Optimization Method | NLMINB | |
| Number of observations | 305 | |
| Free parameters | 51 | |
| Standard errors | Standard | |
| Scaled test | None | |
| Converged | TRUE | |
| Iterations | 136 | |
| Model | CLF =~ cr1 + cr2 + cr3 + cr4 + | |
| f1 + f2 + f3 + f4 + | ||
| pp1 + pp2 + pp3 + pp4 | ||
| CR =~ cr1 + cr2 + cr3 + cr4 | ||
| FB =~ f1 + f2 + f3 + f4 | ||
| PP =~ pp1 + pp2 + pp3 + pp4 | ||
| CLF ~~ 0*CR | ||
| CLF ~~ 0*FB | ||
| CLF ~~ 0*PP | ||
| [3] [4] | ||
| Syntax examples | ||
|---|---|---|
| Aim | Example | Outcome |
| Constraints | ||
| Equality constraint | p1==p2 | Constrain the estimates of p1 and p2 to be equal |
| Linear constraint | p1+p2==2 | Constrain the estimates of p1 and p2 to be equal to 2 |
| Linear constraint | p1+p2+p3==2 | Constrain the estimates for p1,p2, and p3 |
| Constrain coefficients | p1==0 | Fix the coefficient p1 to 0 |
| Inequality Constraint | p1>0 | Estimate the coefficient p1 as larger than 0 |
| Inequality Constraint | p1<3 | Estimate the coefficient p1 as smaller than 3 |
| Constrain intercepts | y1~0 | Fix the y1 intercept to 0 |
| Constrain intercepts | y1~1*0 | Fix the y1 intercept to 1 |
| Non linear constraint | p1*p2=0 | Constrain the estimates such that p1*p2 equals 0 |
| Defined Parameters | ||
| Linear estimates | dp:=p1+p2 | p1 and p2 are free, and their sum is estimated and tested |
| Linear estimates | dp:=(p1+p2)-p3 | p1,p2, and p3 are free, and the specified function is estimated and tested |
| Non linear estimates | aname:=p1^2 | Estimate and test the square of p1 |
| Model tests | |||
|---|---|---|---|
| Label | X² | df | p |
| User Model | 105.554 | 39 | <.001 |
| Baseline Model | 2231.042 | 66 | <.001 |
| Fit indices | ||||
|---|---|---|---|---|
| 95% Confidence Intervals | ||||
| SRMR | RMSEA | Lower | Upper | RMSEA p |
| 0.037 | 0.075 | 0.058 | 0.092 | 0.009 |
| User model versus baseline model | |
|---|---|
| Model | |
| Comparative Fit Index (CFI) | 0.969 |
| Tucker-Lewis Index (TLI) | 0.948 |
| Bentler-Bonett Non-normed Fit Index (NNFI) | 0.948 |
| Relative Noncentrality Index (RNI) | 0.969 |
| Bentler-Bonett Normed Fit Index (NFI) | 0.953 |
| Bollen's Relative Fit Index (RFI) | 0.920 |
| Bollen's Incremental Fit Index (IFI) | 0.970 |
| Parsimony Normed Fit Index (PNFI) | 0.563 |
| Additional fit indices | |
|---|---|
| Model | |
| Hoelter Critical N (CN), α=0.05 | 158.687 |
| Hoelter Critical N (CN), α=0.01 | 181.386 |
| Goodness of Fit Index (GFI) | 0.992 |
| Adjusted Goodness of Fit Index (AGFI) | 0.981 |
| Parsimony Goodness of Fit Index (PGFI) | 0.430 |
| McDonald Fit Index (MFI) | 0.897 |
| Expected Cross-Validation Index (ECVI) | 0.681 |
| Loglikelihood user model (H0) | -4153.357 |
| Loglikelihood unrestricted model (H1) | -4100.579 |
| Akaike (AIC) | 8408.713 |
| Bayesian (BIC) | 8598.449 |
| Sample-size adjusted Bayesian (SABIC) | 8436.702 |
| Measurement model | ||||||||
|---|---|---|---|---|---|---|---|---|
| 95% Confidence Intervals | ||||||||
| Latent | Observed | Estimate | SE | Lower | Upper | β | z | p |
| CLF | cr1 | 1.000 | 0.000 | 1.000 | 1.000 | 0.123 | ||
| cr2 | 1.112 | 0.367 | 0.392 | 1.831 | 0.131 | 3.029 | 0.002 | |
| cr3 | 0.222 | 0.515 | -0.787 | 1.232 | 0.026 | 0.432 | 0.666 | |
| cr4 | 0.853 | 0.472 | -0.072 | 1.779 | 0.095 | 1.807 | 0.071 | |
| f1 | 0.437 | 0.907 | -1.340 | 2.215 | 0.047 | 0.482 | 0.630 | |
| f2 | -0.455 | 0.882 | -2.183 | 1.273 | -0.047 | -0.516 | 0.606 | |
| f3 | 0.865 | 1.006 | -1.108 | 2.837 | 0.094 | 0.859 | 0.390 | |
| f4 | 0.653 | 0.861 | -1.034 | 2.341 | 0.076 | 0.759 | 0.448 | |
| pp1 | -2.855 | 1.756 | -6.297 | 0.587 | -0.392 | -1.625 | 0.104 | |
| pp2 | 2.052 | 2.646 | -3.135 | 7.238 | 0.214 | 0.775 | 0.438 | |
| pp3 | -4.604 | 2.780 | -10.053 | 0.845 | -0.608 | -1.656 | 0.098 | |
| pp4 | 0.395 | 2.174 | -3.866 | 4.657 | 0.041 | 0.182 | 0.856 | |
| CR | cr1 | 1.000 | 0.000 | 1.000 | 1.000 | 0.892 | ||
| cr2 | 1.046 | 0.050 | 0.948 | 1.143 | 0.890 | 21.041 | <.001 | |
| cr3 | 0.889 | 0.057 | 0.778 | 1.000 | 0.746 | 15.731 | <.001 | |
| cr4 | 0.880 | 0.060 | 0.762 | 0.998 | 0.708 | 14.653 | <.001 | |
| FB | f1 | 1.000 | 0.000 | 1.000 | 1.000 | 0.862 | ||
| f2 | 1.098 | 0.054 | 0.993 | 1.204 | 0.907 | 20.447 | <.001 | |
| f3 | 0.960 | 0.051 | 0.860 | 1.060 | 0.845 | 18.845 | <.001 | |
| f4 | 0.800 | 0.052 | 0.698 | 0.901 | 0.747 | 15.469 | <.001 | |
| PP | pp1 | 1.000 | 0.000 | 1.000 | 1.000 | 0.553 | ||
| pp2 | 2.216 | 0.554 | 1.131 | 3.301 | 0.933 | 4.003 | <.001 | |
| pp3 | 1.193 | 0.141 | 0.916 | 1.470 | 0.635 | 8.447 | <.001 | |
| pp4 | 2.038 | 0.403 | 1.249 | 2.827 | 0.850 | 5.061 | <.001 | |
| Variances and Covariances | ||||||||
|---|---|---|---|---|---|---|---|---|
| 95% Confidence Intervals | ||||||||
| Variable 1 | Variable 2 | Estimate | SE | Lower | Upper | β | z | p |
| CLF | CR | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| CLF | FB | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| CLF | PP | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 | ||
| cr1 | cr1 | 0.166 | 0.024 | 0.118 | 0.214 | 0.190 | 6.787 | <.001 |
| cr2 | cr2 | 0.182 | 0.027 | 0.129 | 0.234 | 0.190 | 6.796 | <.001 |
| cr3 | cr3 | 0.436 | 0.040 | 0.357 | 0.515 | 0.442 | 10.774 | <.001 |
| cr4 | cr4 | 0.525 | 0.047 | 0.432 | 0.617 | 0.490 | 11.124 | <.001 |
| f1 | f1 | 0.296 | 0.033 | 0.231 | 0.361 | 0.255 | 8.941 | <.001 |
| f2 | f2 | 0.222 | 0.033 | 0.158 | 0.286 | 0.175 | 6.806 | <.001 |
| f3 | f3 | 0.309 | 0.033 | 0.244 | 0.374 | 0.277 | 9.298 | <.001 |
| f4 | f4 | 0.432 | 0.040 | 0.354 | 0.509 | 0.436 | 10.901 | <.001 |
| pp1 | pp1 | 0.382 | 0.052 | 0.280 | 0.484 | 0.541 | 7.355 | <.001 |
| pp2 | pp2 | 0.101 | 0.134 | -0.162 | 0.364 | 0.083 | 0.750 | 0.453 |
| pp3 | pp3 | 0.173 | 0.096 | -0.015 | 0.362 | 0.228 | 1.800 | 0.072 |
| pp4 | pp4 | 0.343 | 0.085 | 0.175 | 0.510 | 0.277 | 4.014 | <.001 |
| CLF | CLF | 0.013 | 0.015 | -0.016 | 0.043 | 1.000 | 0.888 | 0.375 |
| CR | CR | 0.694 | 0.072 | 0.553 | 0.835 | 1.000 | 9.668 | <.001 |
| FB | FB | 0.864 | 0.094 | 0.680 | 1.048 | 1.000 | 9.191 | <.001 |
| PP | PP | 0.215 | 0.082 | 0.055 | 0.376 | 1.000 | 2.627 | 0.009 |
| CR | FB | -0.052 | 0.049 | -0.148 | 0.044 | -0.067 | -1.056 | 0.291 |
| CR | PP | -0.024 | 0.029 | -0.080 | 0.033 | -0.061 | -0.827 | 0.408 |
| FB | PP | 0.115 | 0.034 | 0.049 | 0.181 | 0.267 | 3.421 | <.001 |
| Intercepts | ||||||
|---|---|---|---|---|---|---|
| 95% Confidence Intervals | ||||||
| Variable | Intercept | SE | Lower | Upper | z | p |
| cr1 | 3.613 | 0.054 | 3.508 | 3.718 | 67.524 | <.001 |
| cr2 | 3.475 | 0.056 | 3.366 | 3.585 | 62.025 | <.001 |
| cr3 | 3.233 | 0.057 | 3.121 | 3.344 | 56.882 | <.001 |
| cr4 | 3.141 | 0.059 | 3.025 | 3.257 | 52.983 | <.001 |
| f1 | 3.341 | 0.062 | 3.220 | 3.462 | 54.118 | <.001 |
| f2 | 3.259 | 0.064 | 3.133 | 3.385 | 50.558 | <.001 |
| f3 | 3.420 | 0.060 | 3.301 | 3.538 | 56.541 | <.001 |
| f4 | 3.620 | 0.057 | 3.508 | 3.731 | 63.540 | <.001 |
| pp1 | 1.370 | 0.048 | 1.276 | 1.465 | 28.498 | <.001 |
| pp2 | 1.957 | 0.063 | 1.834 | 2.081 | 31.018 | <.001 |
| pp3 | 1.485 | 0.050 | 1.387 | 1.583 | 29.729 | <.001 |
| pp4 | 2.000 | 0.064 | 1.875 | 2.125 | 31.375 | <.001 |
| CLF | 0.000 | 0.000 | 0.000 | 0.000 | ||
| CR | 0.000 | 0.000 | 0.000 | 0.000 | ||
| FB | 0.000 | 0.000 | 0.000 | 0.000 | ||
| PP | 0.000 | 0.000 | 0.000 | 0.000 | ||
[5]
[1] The jamovi project (2024). jamovi. (Version 2.6) [Computer Software]. Retrieved from https://www.jamovi.org.
[2] R Core Team (2024). R: A Language and environment for statistical computing. (Version 4.4) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2024-08-07).
[3] Gallucci, M., Jentschke, S. (2021). SEMLj: jamovi SEM Analysis. [jamovi module]. For help please visit https://semlj.github.io/.
[4] Rosseel, Y. (2019). lavaan: An R Package for Structural Equation Modeling. Journal of Statistical Software, 48(2), 1-36. link.
[5] Epskamp S. , Stuber S., Nak J., Veenman M,, Jorgensen T.D. (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. [R Package]. Retrieved from https://CRAN.R-project.org/package=semPlot.