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Related Experiment Videos

[Parameter estimation for Rasch type items that have never been used].

Hideki Toyoda1

  • 1School of Literature, Waseda University, Toyama, Shinjuku-ku, Tokyo 162-8644.

Shinrigaku Kenkyu : the Japanese Journal of Psychology
|July 10, 2002
PubMed
Summary

This study introduces a novel conjoint model using structural equation modeling. The method effectively estimates item response curves and attribute importance, even for unobserved items.

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[Effect sizes, statistical power and sample sizes in "the Japanese Journal of Psychology"].

Shinrigaku kenkyu : The Japanese journal of psychology·2012

Area of Science:

  • Statistics
  • Psychometrics
  • Econometrics

Context:

  • Conjoint analysis is widely used for preference measurement.
  • Traditional methods face limitations in estimating parameters for all possible attribute levels.
  • Structural equation modeling (SEM) offers a flexible framework for complex statistical modeling.

Purpose:

  • To propose a new conjoint model integrating orthogonal arrays with SEM notation.
  • To demonstrate the utility of SEM-based software (LISREL, LISCOMP) for conjoint analysis.
  • To enable the estimation of item response curves and attribute worth values.

Summary:

  • A novel conjoint model is presented, utilizing orthogonal arrays and SEM.
  • The model allows estimation of conjoint measure worth values and item response curves (Rasch and graded response types) using standard SEM software.

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  • A key innovation is the ability to construct response curves for previously unused items.

    • Impact:

    • Provides a flexible and powerful approach to conjoint analysis.
    • Enhances the estimation of item response characteristics, including for unobserved items.
    • Validates the model's performance through comparison with cross-validation data, showing high similarity between constructed and empirical distributions.