About the book
The second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.com/kaplan-materials) provides data sets and code for the book's examples.
New to This Edition
*Utilizes the R interface to Stan--faster and more stable than previously available Bayesian software--for most of the applications discussed.
*Coverage of Hamiltonian MC; Cromwell’s rule; Jeffreys' prior; the LKJ prior for correlation matrices; model evaluation and model comparison, with a critique of the Bayesian information criterion; variational Bayes as an alternative to Markov chain Monte Carlo (MCMC) sampling; and other new topics.
*Chapters on Bayesian variable selection and sparsity, model uncertainty and model averaging, and Bayesian workflow for statistical modeling.
Editions of Bayesian Statistics for the Social Sciences
- Hardcover
- ISBN 9781462553549
- PDF
- ISBN 9781462553556
Read an Excerpt
The second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.com/kaplan-materials) provides data sets and code for the book's examples.
New to This Edition
*Utilizes the R interface to Stan--faster and more stable than previously available Bayesian software--for most of the applications discussed.
*Coverage of Hamiltonian MC; Cromwell’s rule; Jeffreys' prior; the LKJ prior for correlation matrices; model evaluation and model comparison, with a critique of the Bayesian information criterion; variational Bayes as an alternative to Markov chain Monte Carlo (MCMC) sampling; and other new topics.
*Chapters on Bayesian variable selection and sparsity, model uncertainty and model averaging, and Bayesian workflow for statistical modeling.
Frequently Asked Questions
What is Bayesian Statistics for the Social Sciences about?
The second edition of this practical book equips social science researchers to apply the latest Bayesian methodologies to their data analysis problems. It includes new chapters on model uncertainty, Bayesian variable selection and sparsity, and Bayesian workflow for statistical modeling. Clearly explaining frequentist and epistemic probability and prior distributions, the second edition emphasizes use of the open-source RStan software package. The text covers Hamiltonian Monte Carlo, Bayesian linear regression and generalized linear models, model evaluation and comparison, multilevel modeling, models for continuous and categorical latent variables, missing data, and more. Concepts are fully illustrated with worked-through examples from large-scale educational and social science databases, such as the Program for International Student Assessment and the Early Childhood Longitudinal Study. Annotated RStan code appears in screened boxes; the companion website (www.guilford.com/kaplan-materials) provides data sets and code for the book's examples.
New to This Edition
*Utilizes the R interface to Stan--faster and more stable than previously available Bayesian software--for most of the applications discussed.
*Coverage of Hamiltonian MC; Cromwell’s rule; Jeffreys' prior; the LKJ prior for correlation matrices; model evaluation and model comparison, with a critique of the Bayesian information criterion; variational Bayes as an alternative to Markov chain Monte Carlo (MCMC) sampling; and other new topics.
*Chapters on Bayesian variable selection and sparsity, model uncertainty and model averaging, and Bayesian workflow for statistical modeling.
What core themes, tropes, or subjects are explored in Bayesian Statistics for the Social Sciences?
Society and Social Sciences > Sociology and anthropology > Sociology > Social research and statistics
Where can I read a sample of Bayesian Statistics for the Social Sciences?
You can read an official preview of the few pages here https://www.book2look.com/book/9781462553549
Is Bayesian Statistics for the Social Sciences part of a series, and can it be read as a standalone?
Yes it is a part of series Methodology in the Social Sciences Series
Who is/are the Author/s of the book Bayesian Statistics for the Social Sciences?
David Kaplan
What are the ISBN numbers for the physical and digital editions?
Bayesian Statistics for the Social Sciences is available as hardcover(ISBN 9781462553549) and pdf(ISBN 9781462553556)
Where can I buy Bayesian Statistics for the Social Sciences online or support local independent bookshops?
You can buy Bayesian Statistics for the Social Sciences from below
Where can I buy Bayesian Statistics for the Social Sciences?