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

## ----Specify_1----------------------------------------------------------------
library(CLCM)

N <- 80
item.type <- c('Ordinal', 'Nominal', 'Poisson', 'Neg_Binom', 'ZINB', 'ZIP', 'Normal', 'Beta') 
sim.categories.j <- c(4, 4, 30, 30, 30, 30, NA, NA) 
J <- length(item.type)
item.names <- paste0('Item_', 1:J)
Q <- matrix(1, nrow = length(item.type), ncol = 1, dimnames = list(paste0('Item_', 1:length(item.type)), NULL))
K= ncol(Q) 


## ----Specify_2----------------------------------------------------------------

lc.prop <- list('Time_1' = c(0, 1) ) 
tau <- matrix(c(0, 0, 0.4, 0.6), nrow = 2^K, ncol = 2^K, byrow = TRUE)


## ----Generate-----------------------------------------------------------------
set.seed(03102021)
sim.dat <- simulate_clcm(N = N, 
                         number.timepoints = 2, 
                         Q = Q, 
                         item.names = item.names, 
                         item.type = item.type, 
                         categories.j = sim.categories.j, 
                         lc.prop = lc.prop,
                         transition.matrix = tau)


## ----Estimate-----------------------------------------------------------------

mod1 <- clcm(dat = sim.dat$dat, 
             item.type = sim.dat$item.type, 
             item.names = sim.dat$item.names, 
             Q = sim.dat$Q, 
             max.diff = 0.001) 


## ----tau----------------------------------------------------------------------
transition_matrix_clcm(mod = mod1)

## ----Classification-----------------------------------------------------------
lca.hat <- mod1$dat$lca 
lca.true <- mod1$dat$true_lca      
table(lca.true == lca.hat)
prop.table(table(lca.true == lca.hat))
xtabs( ~ lca.true + lca.hat)


## ----Estimate_2---------------------------------------------------------------
mod2 <- clcm(dat = sim.dat$dat, 
             lc.con = list('Time_1' = c(NA, 1), 'Time_2' = c(1, 1)), 
             item.type = sim.dat$item.type, 
             item.names = sim.dat$item.names, 
             Q = sim.dat$Q, 
             max.diff = 0.001) 
      

## ----Fit----------------------------------------------------------------------
unlist( aic_bic_clcm(mod = mod1) )
unlist( aic_bic_clcm(mod = mod2) )

## ----tau_2--------------------------------------------------------------------
transition_matrix_clcm(mod = mod1)
transition_matrix_clcm(mod = mod2)

## ----Classification_2---------------------------------------------------------

lca.hat <- mod2$dat$lca 
lca.true <- mod2$dat$true_lca      
table(lca.true == lca.hat)
prop.table(table(lca.true == lca.hat)) 
xtabs( ~ lca.true + lca.hat)