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August 1, 2000Technometrics

Model Selection and Inference

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Authors

SMSurekha MudivarthyDakota State UniversityMRM. Bhaskara RaoUniversity of North TexasKBKenneth P. BurnhamUtah State University

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Implication

Methodological review examines model selection procedures in statistical analysis, highlighting strategies to ensure valid post-selection inference.

Key Points

  • To review the theoretical foundations and practical implications of statistical model selection and subsequent parameter inference.
  • Reviewed theoretical and computational frameworks for choosing among candidate statistical models.
  • Analyzed the effects of model search procedures on parameter variance and inferential validity.
  • Demonstrated that unaccounted model selection steps introduce post-selection bias and underestimate parameter uncertainty.
  • Highlighted methodological criteria and penalty-based frameworks that optimize the trade-off between model fit and complexity.

Cite This Study

Mudivarthy et al. (2000) studied this question.

synapsesocial.com/papers/6a705ff178a11c550e0a41f1https://doi.org/10.2307/1271104
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Also Consider

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  1. 1Model Selection and Multimodel Inference2003 · 5,560 citations
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