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A Tutorial on Estimating the Precision of Individual Test Scores for Anyone Constructing and Using Psychological Tests

  • Julius M. Pfadt*
  • , Dylan Molenaar
  • , Petra Hurks
  • , Klaas Sijtsma
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

When using tests to assess individuals, precision of individual test scores is of great importance. Although it is generally known that different test scores are measured with varying precision, traditionally, measurement precision is quantified using a single value known as the standard error of measurement. In the practice of testing, the standard error of measurement is used as a one-size-fits-all measure for each test score. This practice emphasizes the need for a conditional precision estimate that shows which scores are precise and which scores lack precision. We discuss several conditional precision estimates based on classical test theory and item response theory, and provide open-source statistical software included in the software package JASP that enables computation of these estimates. Using conditional precision estimates, decisions based on test scores are expected to show less bias than the common unconditional standard error of measurement.
Original languageEnglish
Number of pages22
JournalPsychometrika
DOIs
Publication statusE-pub ahead of print - 9 Jan 2026

Keywords

  • conditional standard error of measurement
  • measurement precision
  • reliability
  • CONDITIONAL STANDARD ERRORS
  • RESPONSE FUNCTION
  • VARIANCE

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