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Ordinal Level of Measurement

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Variable length testing using the ordinal regression model.

Niels Smits1, Matthew D Finkelman

  • 1VU University Amsterdam, The Netherlands.

Statistics in Medicine
|September 17, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new sequential method for health questionnaires that significantly reduces respondent burden. The computer-based approach efficiently obtains sum scores while maintaining high data quality.

Keywords:
computerized testinginterim analysisordinal regressionrespondent burden

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Area of Science:

  • Health Measurement
  • Psychometrics
  • Computerized Adaptive Testing

Background:

  • Traditional health questionnaires rely on sum scores, increasing respondent burden.
  • Computerized adaptive testing (CAT) offers efficiency but has strict requirements.
  • Many existing health questionnaires are incompatible with CAT.

Purpose of the Study:

  • Introduce a novel sequential method for efficient health questionnaire scoring.
  • Develop a computer-based approach that overcomes CAT limitations.
  • Reduce respondent burden without compromising sum score accuracy.

Main Methods:

  • A new sequential method based on ordinal regression is presented.
  • Future scores are predicted from past responses to estimate uncertainty.
  • The procedure terminates when a predefined uncertainty threshold is met.

Main Results:

  • Simulation studies demonstrated substantial reduction in respondent burden.
  • High sum score quality was maintained throughout the assessment.
  • The method proved effective with both simulated and real-world data (CES-D scale).

Conclusions:

  • The novel sequential method offers an efficient alternative to traditional scoring.
  • This approach minimizes respondent burden in health assessments.
  • Further discussion covers the benefits and limitations of this new methodology.