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Using effect sizes for research reporting: examples using item response theory to analyze differential item

Lynne Steinberg1, David Thissen

  • 1Department of Psychology, University of Houston, Houston, TX 770204-5022, USA. lsteinberg@uh.edu

Psychological Methods
|December 13, 2006
PubMed
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Researchers should clearly report effect sizes, which quantify findings beyond statistical significance. This study clarifies three uses of effect sizes and demonstrates their application in item response theory for accurate research reporting.

Area of Science:

  • Psychology
  • Psychometrics

Background:

  • Psychological research increasingly emphasizes reporting effect sizes alongside statistical significance.
  • Confusion exists regarding the distinct applications of effect sizes: power analysis, research synthesis, and research reporting.

Purpose of the Study:

  • To review the different uses of effect sizes in psychological literature.
  • To present a case study on describing effect size for research reporting within item response theory (IRT).

Main Methods:

  • Review of literature on effect size reporting in psychology.
  • Development of a case study using item response theory (IRT) models.
  • Demonstration of expressing effect size through parameter estimates in IRT.

Main Results:

Related Experiment Videos

  • Effect sizes serve distinct roles in power analysis, research synthesis, and reporting.
  • In IRT, parameter estimates from fitted models can directly represent effect sizes.
  • This approach is illustrated with studies detecting differential item functioning.

Conclusions:

  • Clear reporting of effect sizes is crucial for psychological research.
  • Item response theory provides a framework for precise effect size reporting via parameter estimates.
  • Standardizing effect size reporting in IRT enhances research clarity and comparability.