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Related Experiment Video

Updated: Jul 9, 2026

A Two-interval Forced-choice Task for Multisensory Comparisons

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Published on: November 9, 2018

Random Responding Detection in Two Alternative Forced Choice Tests: l _z vs. Optimal Appropriateness Measurement.

Naidan Tu¹, Sean Joo², Stephen Stark³

¹Department of Psychological Sciences, Kansas State University, Manhattan, KS, USA.

Applied Psychological Measurement

|July 8, 2026

Summary

Detecting random responding in Multidimensional Forced Choice (MFC) tests is crucial. The item response theory (IRT)-based person fit statistic lz effectively identifies random response patterns in multi-unidimensional pairwise preference (MUPP) MFC tests using empirical critical values.

Keywords:

aberrant responding detection lz multi-unidimensional pairwise preference (MUPP)multidimensional forced choice (MFC)optimal appropriateness measurement random responding

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Area of Science:

Psychometrics
Educational Measurement
Psychological Testing

Background:

Multidimensional Forced Choice (MFC) tests are used to mitigate faking in high-stakes assessments.
However, MFC tests are still vulnerable to random responding, especially in low-stakes or less consequential settings.
Effective detection of random responding is essential for maintaining the validity of inferences from MFC data.

Purpose of the Study:

To evaluate the effectiveness of the item response theory (IRT)-based person fit statistic lz for detecting random responding in multi-unidimensional pairwise preference (MUPP) MFC tests.
To compare the performance of lz against optimal appropriateness measurement (OAM) as a benchmark.
To identify factors influencing the detection power of lz.

Main Methods:

Two simulation studies were conducted to assess the lz statistic.
Study 1 compared lz with OAM.
Study 2 explored lz performance in a wider range of simulation conditions.

Main Results:

Higher proportions of random items, longer tests, and empirical critical values enhanced lz detection power.
The prevalence of aberrant respondents did not impact lz performance.
OAM was superior to lz only when the random responding model was accurately specified, which is rare in practice.

Conclusions:

The lz statistic, particularly with empirical critical values, is a practical and effective method for detecting random responding in MUPP-based MFC tests.
Findings support the utility of lz in ensuring data validity in various testing contexts.
The study contributes to the literature on aberrant response detection in forced-choice testing formats.