This helper function provides a simple way to retrieve the
lavaan model syntax from a fitted dpm::dpm()
object.
get_syntax(model, print = TRUE)
model | A |
---|---|
Print the syntax to the console so it is formatted properly? Default is TRUE. |
data("WageData", package = "panelr") wages <- panel_data(WageData, id = id, wave = t) fit <- dpm(wks ~ pre(lag(union)) + lag(lwage), data = wages) get_syntax(fit)#> ## Main regressions #> #> wks_2 ~ en1 * union_1 + ex1 * lwage_1 + p1 * wks_1 #> wks_3 ~ en1 * union_2 + ex1 * lwage_2 + p1 * wks_2 #> wks_4 ~ en1 * union_3 + ex1 * lwage_3 + p1 * wks_3 #> wks_5 ~ en1 * union_4 + ex1 * lwage_4 + p1 * wks_4 #> wks_6 ~ en1 * union_5 + ex1 * lwage_5 + p1 * wks_5 #> wks_7 ~ en1 * union_6 + ex1 * lwage_6 + p1 * wks_6 #> #> ## Alpha latent variable (random intercept) #> #> alpha =~ 1 * wks_2 + 1 * wks_3 + 1 * wks_4 + 1 * wks_5 + 1 * wks_6 + 1 * wks_7 #> #> ## Alpha free to covary with observed variables (fixed effects) #> #> alpha ~~ union_1 + union_2 + union_3 + union_4 + union_5 + union_6 + lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + wks_1 #> #> ## Correlating DV errors with future values of predetermined predictors #> #> wks_5 ~~ union_6 #> wks_4 ~~ union_5 + union_6 #> wks_3 ~~ union_4 + union_5 + union_6 #> wks_2 ~~ union_3 + union_4 + union_5 + union_6 #> #> ## Predetermined predictors covariances #> #> union_1 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + wks_1 #> union_2 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + union_1 + wks_1 #> union_3 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + union_1 + union_2 + wks_1 #> union_4 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + union_1 + union_2 + union_3 + wks_1 #> union_5 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + union_1 + union_2 + union_3 + union_4 + wks_1 #> union_6 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + lwage_6 + union_1 + union_2 + union_3 + union_4 + union_5 + wks_1 #> #> ## Exogenous (time varying and invariant) predictors covariances #> #> lwage_1 ~~ wks_1 #> lwage_2 ~~ lwage_1 + wks_1 #> lwage_3 ~~ lwage_1 + lwage_2 + wks_1 #> lwage_4 ~~ lwage_1 + lwage_2 + lwage_3 + wks_1 #> lwage_5 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + wks_1 #> lwage_6 ~~ lwage_1 + lwage_2 + lwage_3 + lwage_4 + lwage_5 + wks_1 #> #> ## DV error variance free to vary across waves #> #> wks_2 ~~ wks_2 #> wks_3 ~~ wks_3 #> wks_4 ~~ wks_4 #> wks_5 ~~ wks_5 #> wks_6 ~~ wks_6 #> wks_7 ~~ wks_7 #> #> ## Let DV variance vary across waves #> #> wks_2 ~ 1 #> wks_3 ~ 1 #> wks_4 ~ 1 #> wks_5 ~ 1 #> wks_6 ~ 1 #> wks_7 ~ 1