parTable.RdShow the parameter table of a fitted model.
parameterTable(object)
parTable(object)An object of class lavaan.
A data.frame containing the model parameters. This is
simply the output of the lavaanify function
coerced to a data.frame (with stringsAsFactors = FALSE).
HS.model <- ' visual =~ x1 + x2 + x3
textual =~ x4 + x5 + x6
speed =~ x7 + x8 + x9 '
fit <- cfa(HS.model, data=HolzingerSwineford1939)
#> Warning: lavaan->lav_model_vcov():
#> The variance-covariance matrix of the estimated parameters (vcov) does not
#> appear to be positive definite! The smallest eigenvalue (= -1.747972e-02)
#> is smaller than zero. This may be a symptom that the model is not
#> identified.
parTable(fit)
#> id lhs op rhs user block group free ustart exo label plabel start
#> 1 1 visual =~ x1 1 1 1 0 1 0 .p1. 1.000
#> 2 2 visual =~ x2 1 1 1 1 NA 0 .p2. 0.778
#> 3 3 visual =~ x3 1 1 1 2 NA 0 .p3. 1.107
#> 4 4 textual =~ x4 1 1 1 0 1 0 .p4. 1.000
#> 5 5 textual =~ x5 1 1 1 3 NA 0 .p5. 1.133
#> 6 6 textual =~ x6 1 1 1 4 NA 0 .p6. 0.924
#> 7 7 speed =~ x7 1 1 1 0 1 0 .p7. 1.000
#> 8 8 speed =~ x8 1 1 1 5 NA 0 .p8. 1.225
#> 9 9 speed =~ x9 1 1 1 6 NA 0 .p9. 0.854
#> 10 10 x1 ~~ x1 0 1 1 7 NA 0 .p10. 0.679
#> 11 11 x2 ~~ x2 0 1 1 8 NA 0 .p11. 0.691
#> 12 12 x3 ~~ x3 0 1 1 9 NA 0 .p12. 0.637
#> 13 13 x4 ~~ x4 0 1 1 10 NA 0 .p13. 0.675
#> 14 14 x5 ~~ x5 0 1 1 11 NA 0 .p14. 0.830
#> 15 15 x6 ~~ x6 0 1 1 12 NA 0 .p15. 0.598
#> 16 16 x7 ~~ x7 0 1 1 13 NA 0 .p16. 0.592
#> 17 17 x8 ~~ x8 0 1 1 14 NA 0 .p17. 0.511
#> 18 18 x9 ~~ x9 0 1 1 15 NA 0 .p18. 0.508
#> 19 19 visual ~~ visual 0 1 1 16 NA 0 .p19. 0.050
#> 20 20 textual ~~ textual 0 1 1 17 NA 0 .p20. 0.050
#> 21 21 speed ~~ speed 0 1 1 18 NA 0 .p21. 0.050
#> 22 22 visual ~~ textual 0 1 1 19 NA 0 .p22. 0.000
#> 23 23 visual ~~ speed 0 1 1 20 NA 0 .p23. 0.000
#> 24 24 textual ~~ speed 0 1 1 21 NA 0 .p24. 0.000
#> est se
#> 1 1.000 0.000
#> 2 0.554 0.094
#> 3 0.729 0.097
#> 4 1.000 0.000
#> 5 1.113 0.062
#> 6 0.926 0.053
#> 7 1.000 0.000
#> 8 1.180 0.079
#> 9 1.082 0.105
#> 10 0.549 0.095
#> 11 1.134 0.104
#> 12 0.844 0.076
#> 13 0.371 0.045
#> 14 0.446 0.053
#> 15 0.356 0.039
#> 16 0.799 0.067
#> 17 0.488 0.068
#> 18 0.566 0.070
#> 19 0.809 0.108
#> 20 0.979 0.109
#> 21 0.384 0.077
#> 22 0.408 0.074
#> 23 0.262 0.058
#> 24 0.173 0.049