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Reducing State Anxiety Using Working Memory Maintenance
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Primary principles in developing scale with Rasch analysis: Portfolio anxiety assessment.

L Tomak1, O Midik2

  • 1Department of Biostatistics and Medical Informatics, Ondokuz Mayis University, Samsun, Turkey.

Nigerian Journal of Clinical Practice
|October 10, 2018
PubMed
Summary

This study demonstrates the Rasch model

Keywords:
Partial credit modelRasch modelportfolioscale development

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Area of Science:

  • Psychometrics
  • Educational Measurement

Background:

  • The Rasch model is a valuable tool for developing and refining measurement scales.
  • Assessing the fit of data to the Rasch model is crucial for scale validation.

Purpose of the Study:

  • To evaluate the fit of a portfolio anxiety scale using the Rasch model.
  • To identify modifications for improving scale fit and psychometric properties.

Main Methods:

  • Applied the partial credit model to a portfolio anxiety scale administered to 171 medical students.
  • Assessed data-Rasch model fit using fit statistics and Person Separation Index (PSI) for reliability.

Main Results:

  • All subscales (satisfaction, writing anxiety, reflection anxiety) demonstrated acceptable fit to the Rasch model.
  • High Person Separation Index values (0.81, 0.73, 0.73) indicated good reliability for the scale subscales.

Conclusions:

  • Rasch analysis confirmed the validity and reliability of the portfolio anxiety scale.
  • The study highlights the utility of Rasch modeling for accurate scale development and adaptation.
  • Fit statistics and graphs are essential for refining scale psychometrics.