Bayesian multilevel models for repeated measures data: a conceptual and practical introduction in R/ Barreda, Santiago & Silbert, Noah

Includes bibliography and index

Introduction: experiments and variables -- Probabilities likelihood and inference -- Fitting bayesian regression models with brms -- Inspecting a 'single group' of observations using a bayesian multilevel model -- Comparing two groups of observations: factors and contrasts -- Variation in parameters (*random effects*) and model comparison -- Comparing many groups interactions and posterior predictive checks -- Varying variances more about priors and prior predictive checks -- Quantitative predictors and their interactions with factors -- Logistic regression and signal detection theory models -- Multiple quantitative predictors dealing with large models and Bayesian ANOVA -- Multinomial and ordinal regression -- Writing up experiments: an investigation of the perception of apparent speaker characteristics from speech acoustics