S4 object with classification statistics.
acc
:Classification accuracy summary statistic across replications.
fp
:False positive summary statistic across replications.
fn
:False negative summary statistic across replications.
cand.acc
:Candidate level accuracy across replications.
cand.fn
:Candidate level false negative across replications.
cand.fp
:Candidate level false positive across replications.
consist
:Classification consistency summary statistic across replications.
cand.consist
:Candidate level classification consistency across replications.
Xij
:Summary matrix of classification probability into all grade combinations.
kappa
:Kappa value for classification accuracy across replications.
item.scores
:Raw item scores used.
bnds
:Grade bounaries used.
tru.grades
:Candidate grades.
tru.scores
:Candidate true scores.
acc.by.grade
:Accuracy by grade.
fp.by.grade
:False positive by grade.
fn.by.grade
:False negative by grade.
consist.by.grade
:Consistency by grade.
labels
:Grade labels.
m.acc
:Mean of Classification accuracy summary statistic across replications.
m.consist
:Mean of Candidate level classification consistency across replications.
m.kappa
:Mean of Kappa value for classification accuracy across replications.
m.fp
:Mean of Candidate level false positive across replications.
m.fn
:Mean of Candidate level false negative across replications.
sd.acc
:SD of Classification accuracy summary statistic across replications.
sd.consist
:SD of Candidate level classification consistency across replications.
sd.kappa
:SD of Kappa value for classification accuracy across replications.
sd.fp
:SD of Candidate level false positive across replications.
sd.fn
:SD of Candidate level false negative across replications.
m.acc.by.grade
:Mean accuracy by grade.
m.fp.by.grade
:Mean false positive by grade.
m.fn.by.grade
:Mean false negative by grade.
m.consist.by.grade
:Mean consistency by grade.
max
:Maximum test score.
Plots.
Summarise stats across replications.
Summary statistics.
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