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Related Experiment Videos

Using item mean squares to evaluate fit to the Rasch model

R M Smith1, R E Schumacker, M J Bush

  • 1Rehabilitation Foundation, Inc., Marianjoy Rehabilitation Hospital and Clinics, Wheaton, IL 60189, USA.

Journal of Outcome Measurement
|July 14, 1998
PubMed
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This study examines Rasch fit mean squares and their transformations. It analyzes how sample size impacts these fit indices, focusing on item fit mean squares across various sample sizes.

Area of Science:

  • Psychometrics
  • Statistical modeling

Background:

  • Rasch fit mean squares were extensively studied in the 1970s, leading to transformations into t-statistics.
  • Sample size significantly influences Rasch fit mean squares, prompting the development of standardized critical values.
  • A shift occurred in the late 1980s/early 1990s towards using untransformed fit mean squares due to sample size sensitivity in t-converted statistics.

Purpose of the Study:

  • To trace the historical evolution of Rasch fit indices and their transformations.
  • To investigate the effect of sample size on both untransformed fit mean squares and their t-transformed counterparts.
  • To focus on item fit mean squares due to the limited impact of sample size on person fit mean squares.

Main Methods:

  • Historical review of Rasch fit index development and transformations.

Related Experiment Videos

  • Empirical examination of the influence of sample size on item fit mean squares.
  • Analysis of the impact of sample size on t-transformed fit mean squares.

    • Main Results:

    • The study details the historical trajectory of Rasch fit mean squares and their t-transformations.
    • It highlights the differential impact of sample size on fit mean squares and their t-transformed values, particularly for item fit.
    • Findings underscore the complexities introduced by sample size variations in Rasch model fit assessment.

    Conclusions:

    • Understanding the historical context and sample size effects is crucial for accurate Rasch model fit interpretation.
    • The paper provides insights into the appropriate use of fit indices in Rasch analysis.
    • Recommendations for best practices in applying fit mean squares and their transformations are implied.