Nothing
library(dplyr)
test_that('profile analysis verb agg',{
db = open_project(test_path('testdata/verbAggression.db'))
f = fit_enorm(db)
p = profiles(db, f, 'behavior')
expect_gt(cor(p$domain_score,p$expected_domain_score), 0.6,
'expected score should have a relation with observed score')
expect_gt(cor(p$domain_score,p$expected_domain_score), cor(p$booklet_score,p$expected_domain_score),
'domain should add extra information')
expect_true(all(p |>
group_by(person_id) |>
summarise(sum_dif = abs(sum(expected_domain_score) - first(booklet_score))) |>
ungroup() |>
pull(sum_dif) < 1e-10),
'expected domains scores need to sum to total test score')
# check inputs work with just parms
pt = profile_tables(f, get_items(db),'situation')
r = get_responses(db,columns=c('person_id','item_id','situation','item_score')) |>
mutate(p=dense_rank(person_id)%%2) |>
filter(!(situation=='Call' & p==1))
p = profiles(r,f,'situation') |>
mutate(p=dense_rank(person_id)%%2) |>
count(p,situation)
expect_true(n_distinct(p$n)==1 && sum(p$situation=='Call')==1 && nrow(p)==7,
label='profiles, unequal categories correctly handled')
f = fit_enorm(db, method='Bayes')
p = profiles(db, f, 'behavior')
expect_gt(cor(p$domain_score,p$expected_domain_score), 0.6,
'expected score should have a relation with observed score (Bayes)')
expect_gt(cor(p$domain_score,p$expected_domain_score), cor(p$booklet_score,p$expected_domain_score),
'domain should add extra information (Bayes)')
expect_true(all(p |>
group_by(person_id) |>
summarise(sum_dif = abs(sum(expected_domain_score) - first(booklet_score))) |>
ungroup() |>
pull(sum_dif) < 1e-10),
'expected domains scores need to sum to total test score (Bayes)')
close_project(db)
})
RcppArmadillo::armadillo_reset_cores()
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