Studies investigating the power of person-fit statistics
often assume that the item parameters that are used
to calculate the statistics are estimated in a sample without
misfitting item score patterns. However, in practical
test applications calibration samples likely will contain
such patterns. In the present study, the influence of the
type and the number of misfitting patterns in the calibration
sample on the detection rate of the ZU3 statistic was
investigated by means of simulated data. An increase in
the number of misfitting simulees resulted in a decrease
in the power of ZU3. Furthermore, the type of misfit and
the test length influenced the power of ZU3. The use of
an iterative procedure to remove the misfitting patterns
from the dataset was investigated. Results suggested that
this method can be used to improve the power of ZU3.
Index terms: aberrance detection, appropriateness measurement,
nonparametric item response theory, person
fit, person-fit statistic ZU3.
Meijer, Rob R. (1996). The influence of the presence of deviant item score patterns on the power of a person-fit statistic. Applied Psychological Measurement, 20, 141-154. doi:10.1177/014662169602000204
Meijer, Rob R..
The influence of the presence of deviant item score patterns on the power of a person-fit statistic.
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