Title
Nonparametric estimation of the plausibility functions of the distractors of vocabulary test items
Abstract
The Level II Vocabulary Subtest of the Iowa
Tests of Basic Skills was analyzed using a two-stage
latent trait approach and an empirical dataset
of 2,356 examinees. First, each of the 43 multiplechoice
test items was scored dichotomously; then,
assuming the (two-parameter) normal ogive model
the item parameters were estimated. The operating
characteristics of the correct answer and of the
three distractors were estimated using a nonparametric
approach called the simple sum procedure
of the conditional probability density
function approach combined with the normal
approach method. Differential information was
provided by the distractors, and these operating
characteristics were named the plausibility functions
of the distractors. The operating characteristic
of the correct answer of each item estimated by
assuming the normal ogive model was compared
with the nonparagnetrically estimated operating
characteristic for model validation. It was concluded
that the nonparametric approach leads to
efficient estimation of the latent trait. Index
terms: distractors, item response theory, latent trait
models, multiple-choice test items, nonparametric estimation,
plausibility functions of distractors.
Identifiers
other: doi:10.1177/014662169401800104
Previously Published Citation
Samejima, Fumiko. (1994). Nonparametric estimation of the plausibility functions of the distractors of vocabulary test items. Applied Psychological Measurement, 18, 35-51. doi:10.1177/014662169401800104
Suggested Citation
Samejima, Fumiko.
(1994).
Nonparametric estimation of the plausibility functions of the distractors of vocabulary test items.
Retrieved from the University of Minnesota Digital Conservancy,
https://hdl.handle.net/11299/116939.