This is just a quick way to get lavaan's summary instead
the more terse summary designed for dpm objects.
lav_summary(x, ...)The dpm object
Other arguments to the lavaan function.
Returns a lavaan.summary object which contains various
model data described in ?lavaan::summary,lavaan-method.
# Load example data
data("WageData", package = "panelr")
# Convert data to panel_data format for ease of use
wages <- panel_data(WageData, id = id, wave = t)
fit <- dpm(wks ~ pre(lag(union)) + lag(lwage) | ed, data = wages)
lav_summary(fit)
#> lavaan 0.6.17 ended normally after 594 iterations
#>
#> Estimator ML
#> Optimization method NLMINB
#> Number of model parameters 179
#> Number of equality constraints 20
#>
#> Number of observations 595
#>
#> Model Test User Model:
#>
#> Test statistic 110.228
#> Degrees of freedom 71
#> P-value (Chi-square) 0.002
#>
#> Parameter Estimates:
#>
#> Standard errors Standard
#> Information Expected
#> Information saturated (h1) model Structured
#>
#> Latent Variables:
#> Estimate Std.Err z-value P(>|z|)
#> alpha =~
#> wks_2 1.000
#> wks_3 1.000
#> wks_4 1.000
#> wks_5 1.000
#> wks_6 1.000
#> wks_7 1.000
#>
#> Regressions:
#> Estimate Std.Err z-value P(>|z|)
#> wks_2 ~
#> union_1 (en1) -1.191 0.513 -2.321 0.020
#> lwage_1 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_1 (p1) 0.187 0.020 9.275 0.000
#> wks_3 ~
#> union_2 (en1) -1.191 0.513 -2.321 0.020
#> lwage_2 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_2 (p1) 0.187 0.020 9.275 0.000
#> wks_4 ~
#> union_3 (en1) -1.191 0.513 -2.321 0.020
#> lwage_3 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_3 (p1) 0.187 0.020 9.275 0.000
#> wks_5 ~
#> union_4 (en1) -1.191 0.513 -2.321 0.020
#> lwage_4 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_4 (p1) 0.187 0.020 9.275 0.000
#> wks_6 ~
#> union_5 (en1) -1.191 0.513 -2.321 0.020
#> lwage_5 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_5 (p1) 0.187 0.020 9.275 0.000
#> wks_7 ~
#> union_6 (en1) -1.191 0.513 -2.321 0.020
#> lwage_6 (ex1) 0.642 0.484 1.327 0.185
#> ed (c1) -0.112 0.056 -2.011 0.044
#> wks_6 (p1) 0.187 0.020 9.275 0.000
#>
#> Covariances:
#> Estimate Std.Err z-value P(>|z|)
#> alpha ~~
#> union_1 -0.116 0.109 -1.065 0.287
#> union_2 -0.106 0.111 -0.953 0.341
#> union_3 -0.074 0.114 -0.651 0.515
#> union_4 -0.073 0.116 -0.627 0.530
#> union_5 -0.094 0.119 -0.786 0.432
#> union_6 -0.083 0.120 -0.694 0.488
#> lwage_1 -0.000 0.068 -0.006 0.996
#> lwage_2 0.001 0.064 0.008 0.993
#> lwage_3 0.025 0.078 0.324 0.746
#> lwage_4 0.054 0.076 0.715 0.475
#> lwage_5 0.029 0.073 0.390 0.697
#> lwage_6 0.034 0.073 0.466 0.641
#> wks_1 3.987 0.808 4.938 0.000
#> .wks_5 ~~
#> union_6 0.045 0.034 1.294 0.196
#> .wks_4 ~~
#> union_5 -0.024 0.035 -0.683 0.495
#> union_6 0.020 0.040 0.502 0.616
#> .wks_3 ~~
#> union_4 0.022 0.033 0.661 0.509
#> union_5 0.001 0.043 0.019 0.985
#> union_6 -0.004 0.047 -0.084 0.933
#> .wks_2 ~~
#> union_3 -0.100 0.041 -2.444 0.015
#> union_4 -0.078 0.043 -1.823 0.068
#> union_5 -0.115 0.052 -2.214 0.027
#> union_6 -0.067 0.055 -1.216 0.224
#> union_1 ~~
#> ed -0.379 0.057 -6.649 0.000
#> lwage_1 0.012 0.008 1.507 0.132
#> lwage_2 0.015 0.007 2.031 0.042
#> lwage_3 -0.001 0.009 -0.169 0.866
#> lwage_4 -0.006 0.009 -0.716 0.474
#> lwage_5 -0.003 0.008 -0.341 0.733
#> lwage_6 -0.001 0.008 -0.100 0.920
#> wks_1 -0.401 0.124 -3.227 0.001
#> ed ~~
#> union_2 -0.346 0.056 -6.154 0.000
#> lwage_1 ~~
#> union_2 0.010 0.008 1.360 0.174
#> union_2 ~~
#> lwage_2 0.013 0.007 1.813 0.070
#> lwage_3 -0.002 0.009 -0.242 0.809
#> lwage_4 -0.007 0.009 -0.777 0.437
#> lwage_5 -0.002 0.008 -0.292 0.771
#> lwage_6 0.002 0.008 0.246 0.806
#> union_1 ~~
#> union_2 0.210 0.013 16.512 0.000
#> wks_1 ~~
#> union_2 -0.449 0.123 -3.638 0.000
#> ed ~~
#> union_3 -0.333 0.057 -5.877 0.000
#> lwage_1 ~~
#> union_3 0.006 0.008 0.782 0.434
#> lwage_2 ~~
#> union_3 0.008 0.007 1.141 0.254
#> union_3 ~~
#> lwage_3 -0.004 0.009 -0.420 0.675
#> lwage_4 -0.007 0.009 -0.779 0.436
#> lwage_5 -0.004 0.008 -0.471 0.638
#> lwage_6 0.004 0.008 0.435 0.664
#> union_1 ~~
#> union_3 0.199 0.013 15.911 0.000
#> union_2 ~~
#> union_3 0.206 0.013 16.274 0.000
#> wks_1 ~~
#> union_3 -0.595 0.126 -4.725 0.000
#> ed ~~
#> union_4 -0.384 0.057 -6.694 0.000
#> lwage_1 ~~
#> union_4 0.004 0.008 0.455 0.649
#> lwage_2 ~~
#> union_4 0.007 0.007 0.915 0.360
#> lwage_3 ~~
#> union_4 -0.006 0.009 -0.719 0.472
#> union_4 ~~
#> lwage_4 -0.010 0.009 -1.114 0.265
#> lwage_5 -0.006 0.008 -0.717 0.473
#> lwage_6 0.001 0.008 0.155 0.877
#> union_1 ~~
#> union_4 0.201 0.013 15.983 0.000
#> union_2 ~~
#> union_4 0.205 0.013 16.202 0.000
#> union_3 ~~
#> union_4 0.211 0.013 16.407 0.000
#> wks_1 ~~
#> union_4 -0.552 0.126 -4.389 0.000
#> ed ~~
#> union_5 -0.348 0.057 -6.129 0.000
#> lwage_1 ~~
#> union_5 0.000 0.008 0.024 0.981
#> lwage_2 ~~
#> union_5 0.005 0.007 0.696 0.487
#> lwage_3 ~~
#> union_5 -0.008 0.009 -0.872 0.383
#> lwage_4 ~~
#> union_5 -0.010 0.009 -1.172 0.241
#> union_5 ~~
#> lwage_5 -0.008 0.008 -0.907 0.365
#> lwage_6 -0.002 0.008 -0.213 0.831
#> union_1 ~~
#> union_5 0.190 0.012 15.507 0.000
#> union_2 ~~
#> union_5 0.197 0.012 15.884 0.000
#> union_3 ~~
#> union_5 0.202 0.013 16.040 0.000
#> union_4 ~~
#> union_5 0.210 0.013 16.337 0.000
#> wks_1 ~~
#> union_5 -0.586 0.126 -4.664 0.000
#> ed ~~
#> union_6 -0.370 0.057 -6.506 0.000
#> lwage_1 ~~
#> union_6 0.003 0.008 0.368 0.713
#> lwage_2 ~~
#> union_6 0.006 0.007 0.909 0.363
#> lwage_3 ~~
#> union_6 -0.008 0.009 -0.856 0.392
#> lwage_4 ~~
#> union_6 -0.009 0.009 -1.061 0.289
#> lwage_5 ~~
#> union_6 -0.006 0.008 -0.758 0.448
#> union_6 ~~
#> lwage_6 -0.000 0.008 -0.022 0.983
#> union_1 ~~
#> union_6 0.188 0.012 15.427 0.000
#> union_2 ~~
#> union_6 0.194 0.012 15.804 0.000
#> union_3 ~~
#> union_6 0.198 0.012 15.866 0.000
#> union_4 ~~
#> union_6 0.207 0.013 16.253 0.000
#> union_5 ~~
#> union_6 0.214 0.013 16.609 0.000
#> wks_1 ~~
#> union_6 -0.455 0.124 -3.667 0.000
#> lwage_1 ~~
#> ed 0.426 0.048 8.944 0.000
#> wks_1 0.316 0.100 3.152 0.002
#> ed ~~
#> lwage_2 0.422 0.045 9.399 0.000
#> lwage_1 ~~
#> lwage_2 0.132 0.008 16.724 0.000
#> wks_1 ~~
#> lwage_2 0.256 0.093 2.745 0.006
#> ed ~~
#> lwage_3 0.526 0.055 9.505 0.000
#> lwage_1 ~~
#> lwage_3 0.149 0.009 15.898 0.000
#> lwage_2 ~~
#> lwage_3 0.140 0.009 15.976 0.000
#> wks_1 ~~
#> lwage_3 0.364 0.115 3.156 0.002
#> ed ~~
#> lwage_4 0.550 0.055 9.980 0.000
#> lwage_1 ~~
#> lwage_4 0.145 0.009 15.760 0.000
#> lwage_2 ~~
#> lwage_4 0.138 0.009 15.948 0.000
#> lwage_3 ~~
#> lwage_4 0.177 0.011 16.307 0.000
#> wks_1 ~~
#> lwage_4 0.359 0.114 3.157 0.002
#> ed ~~
#> lwage_5 0.540 0.053 10.148 0.000
#> lwage_1 ~~
#> lwage_5 0.140 0.009 15.817 0.000
#> lwage_2 ~~
#> lwage_5 0.134 0.008 16.033 0.000
#> lwage_3 ~~
#> lwage_5 0.167 0.010 16.149 0.000
#> lwage_4 ~~
#> lwage_5 0.169 0.010 16.385 0.000
#> wks_1 ~~
#> lwage_5 0.308 0.109 2.819 0.005
#> ed ~~
#> lwage_6 0.524 0.053 9.893 0.000
#> lwage_1 ~~
#> lwage_6 0.134 0.009 15.425 0.000
#> lwage_2 ~~
#> lwage_6 0.128 0.008 15.631 0.000
#> lwage_3 ~~
#> lwage_6 0.162 0.010 15.853 0.000
#> lwage_4 ~~
#> lwage_6 0.165 0.010 16.159 0.000
#> lwage_5 ~~
#> lwage_6 0.166 0.010 16.584 0.000
#> wks_1 ~~
#> lwage_6 0.270 0.109 2.475 0.013
#> ed ~~
#> wks_1 0.067 0.714 0.094 0.925
#>
#> Intercepts:
#> Estimate Std.Err z-value P(>|z|)
#> .wks_2 36.140 2.893 12.492 0.000
#> .wks_3 35.953 2.936 12.247 0.000
#> .wks_4 36.037 2.995 12.033 0.000
#> .wks_5 35.719 3.041 11.745 0.000
#> .wks_6 35.464 3.080 11.514 0.000
#> .wks_7 35.177 3.114 11.297 0.000
#> union_1 0.361 0.020 18.348 0.000
#> lwage_1 6.375 0.016 400.689 0.000
#> ed 12.845 0.114 112.400 0.000
#> wks_1 46.281 0.256 180.680 0.000
#> union_2 0.348 0.020 17.817 0.000
#> lwage_2 6.465 0.015 435.167 0.000
#> union_3 0.370 0.020 18.697 0.000
#> lwage_3 6.597 0.018 360.533 0.000
#> union_4 0.373 0.020 18.820 0.000
#> lwage_4 6.696 0.018 370.896 0.000
#> union_5 0.366 0.020 18.550 0.000
#> lwage_5 6.786 0.017 390.740 0.000
#> union_6 0.363 0.020 18.459 0.000
#> lwage_6 6.864 0.017 395.200 0.000
#>
#> Variances:
#> Estimate Std.Err z-value P(>|z|)
#> .wks_2 18.724 1.200 15.601 0.000
#> .wks_3 14.630 0.966 15.144 0.000
#> .wks_4 11.995 0.814 14.744 0.000
#> .wks_5 16.314 1.057 15.430 0.000
#> .wks_6 16.400 1.060 15.478 0.000
#> .wks_7 17.846 1.137 15.702 0.000
#> union_1 0.231 0.013 17.248 0.000
#> lwage_1 0.151 0.009 17.248 0.000
#> ed 7.771 0.451 17.248 0.000
#> wks_1 39.039 2.263 17.248 0.000
#> union_2 0.227 0.013 17.248 0.000
#> lwage_2 0.131 0.008 17.248 0.000
#> union_3 0.233 0.013 17.276 0.000
#> lwage_3 0.199 0.012 17.248 0.000
#> union_4 0.234 0.014 17.268 0.000
#> lwage_4 0.194 0.011 17.248 0.000
#> union_5 0.232 0.013 17.281 0.000
#> lwage_5 0.179 0.010 17.248 0.000
#> union_6 0.230 0.013 17.271 0.000
#> lwage_6 0.179 0.010 17.248 0.000
#> alpha 4.422 0.553 7.999 0.000
#>