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Showing 1 to 1 of 1 for “"Crossed-Random Effects Models, convergence, MLE, REML, Bayesian model estimation"”.

  1. A Bayesian solution to non-convergence of crossed random effects models

    … within combinations of subjects and stimuli, crossed random effects models simultaneously take into account both fixed effects and random effects of the subjects and stimuli; however, maximum likelihood estimation (MLE) and restricted maximum likelihood (REML) estimation often encounter …

    uiuc Repository record for A Bayesian solution to non-convergence of crossed random effects models (opens in a new tab)