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Analysis of longitudinal data: random coefficient regression modelling

C M Rutter1, R M Elashoff

  • 1Department of Health Care Policy, Harvard Medical School, Boston, MA 02115.

Statistics in Medicine
|June 30, 1994
PubMed
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This review covers random coefficient regression (RCR) models, focusing on practical applications and fitting methods. It addresses data analysis for exponential family distributions, fixed effects interpretation, and model assessment for robust statistical inference.

Area of Science:

  • Statistics
  • Econometrics
  • Biostatistics

Background:

  • Random coefficient regression (RCR) models are valuable for analyzing data with heterogeneity.
  • Existing literature often focuses on theoretical aspects, with less emphasis on practical application and fitting methods.

Purpose of the Study:

  • To provide a comprehensive review of random coefficient regression (RCR) models from an applications perspective.
  • To detail methods for fitting RCR models, particularly for data with exponential family distributions.
  • To discuss the interpretation of model components and practical challenges in model assessment.

Main Methods:

  • Review of established and emerging methods for fitting RCR models.
  • Presentation of techniques applicable to exponential family distributions, including Gaussian.

Related Experiment Videos

  • Discussion of computational approaches for estimation and inference.
  • Exploration of strategies for model selection and assessment.

    • Main Results:

    • RCR models offer flexibility in capturing individual-level variation.
    • Accurate variance estimation and robustness to covariance misspecification are critical for testing fixed effects.
    • Recommended approaches for model fitting, interpretation, and assessment are presented.

    Conclusions:

    • RCR models provide a powerful framework for statistical analysis when accounting for varying coefficients.
    • Careful consideration of estimation, variance estimation, and model selection is essential for reliable application.
    • The review equips practitioners with practical guidance for utilizing RCR models effectively.