Prediction With Mixed Effects Models: A Monte Carlo Simulation Study.

Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare seve...

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Publicado en:Educational & Psychological Measurement Vol. 81; no. 6; pp. 1118 - 1143
Autores principales: Mangino, Anthony A., Finch, W. Holmes
Formato: Artículo
Publicado: Sage Publications Inc. Dec2021
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Dec2021
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      pub: Sage Publications Inc.
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        10.1177/0013164421992818
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        atl: Prediction With Mixed Effects Models: A Monte Carlo Simulation Study.
      aug:
        au:
          Mangino, Anthony A.
          Finch, W. Holmes
        affil: Ball State University, Teachers College, Muncie, IN, USA
      su:
        Computer simulation
        Analysis of variance
        Sample size (Statistics)
        Random forest algorithms
        Descriptive statistics
        Statistical models
        Artificial neural networks
        Data analysis software
        Algorithms
      sug:
        subj:
          Computer simulation
          Analysis of variance
          Sample size (Statistics)
          Random forest algorithms
          Descriptive statistics
          Statistical models
          Artificial neural networks
          Data analysis software
          Algorithms
      keyword:
        classification
        multilevel modeling
        predictive modeling
        classification
        multilevel modeling
        predictive modeling
      ab: Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms across several varied data conditions for the purpose of prediction. Among these models, the panel neural network and Bayesian generalized mixed effects model (multilevel Bayes) consistently yielded the highest prediction accuracy in test data across nearly all data conditions.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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