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Psychometric Consequences of Subpopulation Item Parameter Drift.

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Subpopulation item parameter drift (SIPD) occurs when item changes over time affect specific examinee groups. This study shows SIPD in anchor items leads to bias and lack of invariance in psychometric outcomes.

Keywords:
differential item functioningfairnessinvarianceitem parameter drift

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Area of Science:

  • Psychometrics
  • Educational Measurement
  • Item Response Theory

Background:

  • Item parameter drift (IPD) and differential item functioning (DIF) are known sources of measurement bias.
  • However, changes in item parameters that specifically affect subpopulations over time (SIPD) have not been fully explored.
  • Anchor items are crucial for equating and maintaining measurement invariance across test administrations.

Purpose of the Study:

  • To define and introduce the concept of subpopulation item parameter drift (SIPD).
  • To hypothesize and investigate the association between SIPD in anchor items and psychometric outcomes.
  • To determine if SIPD explains bias beyond traditional IPD and DIF.

Main Methods:

  • Defined SIPD as time-dependent changes in item parameters varying by examinee subpopulations.
  • Hypothesized SIPD in anchor items would correlate with lack of invariance in dimensionality, scaling coefficients, and ability estimates.
  • Analyzed psychometric data to assess the impact of SIPD on measurement invariance.

Main Results:

  • SIPD in anchor items was significantly associated with a lack of invariance in the dimensionality structure of an anchor test.
  • SIPD was also linked to a lack of invariance in scaling coefficients across different subpopulations.
  • Furthermore, SIPD was found to be associated with a lack of invariance in ability estimates.

Conclusions:

  • SIPD in anchor items is a critical factor contributing to measurement bias and lack of invariance.
  • The effects of SIPD extend beyond the phenomena explained by standard IPD and DIF.
  • Understanding and addressing SIPD is essential for maintaining accurate and fair assessments over time, especially in longitudinal studies and large-scale testing programs.