simulation/test_sim_4_7.r

In sooyongl/ESS:

# rm(list = ls())
library(ESS)
library(foreach)
library(tidyverse)
select <- dplyr::select

# Even distribution of RP_i ----------------------------------
true_data <- genSimData(
  item_loc_range = c(100, 500),
  loc_by = 1,
  nitem = 100,
  nlevel = 3,
  correlation = 0.5,
  type_seq = "same")

c(level2=head(which(true_data$Operational_Lv == "Level2"),1),level3=
head(which(true_data$Operational_Lv == "Level3"),1))

test_data_WESS <- simEstCutScore(true_data, WESS = T)
test_data_WESS$selected_CP

mkPlot(test_data_WESS$res, WESS = T);
estCor(test_data_WESS$res)

psych::cohen.kappa(data.frame(test_data_WESS$res$Operational_Lv, test_data_WESS$res$ALD))

table(OPL=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

test_data_CESS <- simEstCutScore(true_data, WESS = F)
test_data_CESS$selected_CP

mkPlot(.data = test_data_CESS$res, WESS = F);
estCor(test_data_CESS$res)

psych::cohen.kappa(data.frame(test_data_CESS$res$Operational_Lv, test_data_CESS$res$ALD))

table(OP=test_data_CESS$res$Operational_Lv, ALD=test_data_CESS$res$ALD)

true_data <- genSimData(item_loc_range = c(100, 500), loc_by = 1, nitem = 100, nlevel = 3, correlation = 0.5, type_seq = "little")

test_data_WESS <- simEstCutScore(true_data, WESS = T)
test_data_WESS$selected_CP

mkPlot(test_data_WESS$res, WESS = T);
estCor(test_data_WESS$res)

table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

test_data_CESS <- simEstCutScore(true_data, WESS = F)
test_data_CESS$selected_CP

mkPlot(test_data_CESS$res, WESS = F);
estCor(test_data_CESS$res)


table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)


true_data <- genSimData(item_loc_range = c(100, 500), loc_by = 1, nitem = 100, nlevel = 3, correlation = 0.5, type_seq = "random")

c(level2=head(which(true_data$Operational_Lv == "Level2"),1),level3=
    head(which(true_data$Operational_Lv == "Level3"),1))


test_data_WESS <- simEstCutScore(true_data, WESS = T)
test_data_WESS$selected_CP
mkPlot(test_data_WESS$res, WESS = T);
estCor(test_data_WESS$res)

table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

test_data_CESS <- simEstCutScore(true_data, WESS = F)
test_data_CESS$selected_CP
mkPlot(test_data_CESS$res, WESS = F);
estCor(test_data_CESS$res)

table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

# Large number of items----------------------------------
true_data <- genSimData(item_loc_range = c(100, 500), loc_by = 1, nitem = 1000, nlevel = 3, correlation = 0.5, type_seq = "random")


c(level2=head(which(true_data$Operational_Lv == "Level2"),1),level3=
    head(which(true_data$Operational_Lv == "Level3"),1))


test_data_WESS <- simEstCutScore(true_data, WESS = T)
test_data_WESS$selected_CP

mkPlot(test_data_WESS$res, WESS = T);
estCor(test_data_WESS$res)

table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

table(OP=test_data_WESS$res$Operational_Lv, true_data$Operational_Lv)

test_data_CESS <- simEstCutScore(true_data, WESS = F)
test_data_CESS$selected_CP

mkPlot(test_data_CESS$res, WESS = F);
estCor(test_data_CESS$res)

table(OP=test_data_CESS$res$Operational_Lv, ALD=test_data_CESS$res$ALD)

table(OP=test_data_CESS$res$Operational_Lv, true_data$Operational_Lv)

# High correlation between L_i^((ALD) ) and RP_i----------------------------------




# Low frequency/prevalence of outliers----------------------------------


# more levels----------------------------------

true_data <- genSimData(item_loc_range = c(100, 500), loc_by = 1, nitem = 1000, nlevel = 5, correlation = 0.5, type_seq = "random")

test_data_WESS <- simEstCutScore(true_data, WESS = T)
test_data_WESS$selected_CP

mkPlot(test_data_WESS$res, WESS = T);
estCor(test_data_WESS$res)

table(OP=test_data_WESS$res$Operational_Lv, ALD=test_data_WESS$res$ALD)

test_data_CESS <- simEstCutScore(true_data, WESS = F)
test_data_CESS$selected_CP

mkPlot(test_data_CESS$res, WESS = F);
estCor(test_data_CESS$res)

table(OP=test_data_CESS$res$Operational_Lv, ALD=test_data_CESS$res$ALD)