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Routledge Bayesian Multilevel Models for Repeated Measures Data in R

Amazon

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Description

This comprehensive guide introduces Bayesian multilevel models using R, brms, and Stan programming language, specifically designed for analysing repeated measures data. The book presents 13 well-structured chapters with fully worked analyses that progress from simple two-group comparisons to advanced multinomial regression models with random effects. Written for active learners, this resource combines conceptual foundations with practical applications, making it ideal for researchers and statisticians seeking to master Bayesian methods for complex data structures. The focus on repeated measures data and step-by-step model building ensures readers develop both theoretical understanding and hands-on competency with modern statistical techniques.

Key Features

Covers 13 chapters progressing from basic two-group comparisons to multinomial regression models with random effects.

Features fully worked analyses of repeated measures data using brms and Stan programming language in R.

Emphasises active learning through practical examples that build progressively more complex Bayesian models.

Authored by Routledge and designed for researchers working with repeated measures and longitudinal data.

Combines conceptual introduction to Bayesian statistics with applied demonstrations of multilevel modelling techniques.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
18 May 2023
Listed Since
28 October 2022

Barcode

No barcode data available

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