library(eRm)
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_mloef: p-value 0.088, alpha: 0.05",{
testthat::expect_equal(length(
exhaustiveRasch::test_mloef(items=1:5, dset=ADL, na.rm=TRUE, modelType="RM",
alpha=0.05, estimation_param = estimation_control(est="eRm"))),
expected=3)})
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
testthat::test_that("test_mloef: p-value 0.088, alpha: 0.05; na.rm=FALSE",{
testthat::expect_equal(length(
exhaustiveRasch::test_mloef(items=1:5, dset=ADL,
na.rm=FALSE, modelType="RM",
alpha=0.05,
estimation_param=
estimation_control(est="eRm"))),
expected=3)})
# list of 3 is returned (item combinations, fit rasch model and ppar)
data(ADL)
firstrun <- exhaustiveRasch::test_mloef(
items=1:5, dset=ADL,
na.rm=FALSE, modelType="RM",
alpha=0.05,
estimation_param=
estimation_control(est="eRm"))
testthat::test_that("test_mloef: p-value 0.088, alpha: 0.05;
with pre-fitted model in 'items' parameter",{
testthat::expect_equal(length(
exhaustiveRasch::test_mloef(items=firstrun, dset=ADL,
na.rm=FALSE, modelType="RM",
alpha=0.05,
estimation_param=
estimation_control(est="eRm"))),
expected=3)})
# empty list is returned
data(ADL)
testthat::test_that("test_mloef: p-value 0.088, alpha: 0.1",{
testthat::expect_equal(length(
exhaustiveRasch::test_mloef(items=1:5, dset=ADL, na.rm=TRUE, modelType="RM",
estimation_param=
estimation_control(est="eRm"))),
expected=0)})
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