## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ----setup--------------------------------------------------------------------
library(plavaan)
library(lavaan)

## -----------------------------------------------------------------------------
# Load the PoliticalDemocracy data
data("PoliticalDemocracy", package = "lavaan")
# Recode y2 and y6 to have negative loadings
PoliticalDemocracy$y2 <- -PoliticalDemocracy$y2
PoliticalDemocracy$y6 <- -PoliticalDemocracy$y6
# Configural invariance (pretend y7 is not available in dem65),
# and freely estimated latent means and variances
config_mod <- "
  dem60 =~ y1 + y2 + y3 + y4
  dem65 =~ y5 + y6 +      y8
  dem60 ~~ dem65
  dem60 ~~ 1 * dem60
  dem65 ~~ NA * dem65
  dem60 ~ 0
  dem65 ~ NA * 1
  y1 ~~ y5
  y2 ~~ y6
  y4 ~~ y8
"
fit_dry <- cfa(config_mod, data = PoliticalDemocracy, auto.fix.first = FALSE,
               do.fit = FALSE)

## -----------------------------------------------------------------------------
parTable(fit_dry)
# Create matrix to indicate the same item loadings across groups/time in columns for
# penalization on the pairwise differences
ld_mat <- rbind(1:4, c(5:6, NA, 7))
int_mat <- rbind(21:24, c(25:26, NA, 27))
fit_pen <- penalized_est(
  fit_dry, w = .03, pen_diff_id = list(loadings = ld_mat, intercepts = int_mat),
  se = "robust.huber.white"
)
summary(fit_pen)