Statistical methods to assess the congruence
between an item response pattern and a specified
item response theory model have recently proliferated.
This "person fit" research has focused
on the question: To what extent can person-fit indices
identify well-defined forms of aberrant item
response? This study extended previous person-fit
research in two ways. First, an unexplored model
for generating aberrant response patterns was
explicated. The data-generation model is based on
the theory that aberrant item responses result in
less psychometric information for the individual
than predicated by the parameters of a specified
response model. Second, the proposed response
aberrancy generation model was implemented to
investigate how the aberrancy detection power of a
person-fit statistic is influenced by test properties
(e.g., the spread of item difficulties). Results indicated
that detecting aberrant response patterns
was especially problematic for tests with less than
20 items, and for tests with limited ranges of item
difficulty. An applied consequence of these results
is that certain types of test designs (e.g., peaked
tests) and administration procedures (e.g., adaptive
tests) potentially act to limit the detection of
aberrant item responses. Index terms: aberrancy
detection, IRT, person fit, response aberrancy, Z₁ index.
Reise, Steven P & Due, Allan M. (1991). The influence of test characteristics on the detection of aberrant response patterns. Applied Psychological Measurement, 15, 217-226. doi:10.1177/014662169101500301
Reise, Steven P.; Due, Allan M..
The influence of test characteristics on the detection of aberrant response patterns.
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