library(eRm)
#Itemfit Statistics:
# Chisq df p-value Outfit MSQ Infit MSQ Outfit t Infit t Discrim
#V12 182.432 258 1.000 0.704 0.783 -1.835 -3.064 0.294
#V22 138.778 258 1.000 0.536 0.802 -2.181 -2.441 0.007
#V27 225.681 258 0.927 0.871 0.910 -0.541 -1.146 -0.062
#V36 137.030 258 1.000 0.529 0.707 -3.602 -4.180 0.436
# only MSQ infits
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_itemfit: MSQ infits 0.7-1.3",{
testthat::expect_equal(length(exhaustiveRasch::test_itemfit(
items=c(6,7,12,14), dset=ADL, na.rm=TRUE, modelType="RM",
exhaustiveRasch::itemfit_control(
outfits = FALSE, use.pval = FALSE),
estimation_param= estimation_control(est="eRm"))),
expected=3)})
# only MSQ infits
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_itemfit: MSQ infits 0.7-1.3; na.rm=FALSE",{
testthat::expect_equal(length(exhaustiveRasch::test_itemfit(
items=c(6,7,12,14), dset=ADL, na.rm=FALSE, modelType="RM",
exhaustiveRasch::itemfit_control(
outfits = FALSE, use.pval = FALSE),
estimation_param= estimation_control(est="psychotools"))),
expected=3)})
# MSQ infits and outfits: empty list is returned
data(ADL)
testthat::test_that("test_itemfit: MSQ in- and outfits 0.7-1.3",{
testthat::expect_equal(length(exhaustiveRasch::test_itemfit(
items=c(6,7,12,14), dset=ADL, na.rm=TRUE, modelType="RM",
exhaustiveRasch::itemfit_control(
outfits = TRUE, use.pval = FALSE),
estimation_param= estimation_control(est="psychotools"))),
expected=0)})
# MSQ infits and p-values
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_itemfit: MSQ infits and p-values",{
testthat::expect_equal(length(exhaustiveRasch::test_itemfit(
items=c(6,7,12,14), dset=ADL, na.rm=TRUE, modelType="RM",
exhaustiveRasch::itemfit_control(
outfits = FALSE, use.pval = TRUE),
estimation_param= estimation_control(est="psychotools"))),
expected=3)})
# standardized infits and outfits: empty list is returned
data(ADL)
testthat::test_that("test_itemfit: std in- and outfits",{
testthat::expect_equal(length(exhaustiveRasch::test_itemfit(
items=c(6,7,12,14), dset=ADL, na.rm=TRUE, modelType="RM",
exhaustiveRasch::itemfit_control(
outfits = TRUE, use.pval = FALSE,
zstd=TRUE),
estimation_param= estimation_control(est="psychotools"))),
expected=0)})
# only MSQ infits with pre-fit model in the 'itemss' parameter:
# list of 3 is returned (item combinations, fit rasch model and ppar)
# pairwise
firstrun <- test_itemfit(
items=c(1,2,3,4), dset=ADL, na.rm=TRUE, modelType="RM",
itemfit_control(outfits = FALSE, use.pval = FALSE, lowerMSQ = 0,5, upperMSQ = 1.5),
estimation_param= estimation_control(est="pairwise"))
testthat::test_that("test_itemfit: pre-fit model",{
testthat::expect_equal(length(test_itemfit(
items=firstrun, dset=ADL, na.rm=TRUE, modelType="RM",
itemfit_control(outfits = FALSE, use.pval = FALSE, lowerMSQ = 0,5, upperMSQ = 1.5),
estimation_param= estimation_control(est="pairwise"))),
expected=3)})
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