Introduction To Applied Bayesian Statistics And Estimation For Social Scientists (Statistics For Social And Behavioral Sciences)

Introduction To Applied Bayesian Statistics And Estimation For Social Scientists (Statistics For Social And Behavioral Sciences)

This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.ReviewFrom the reviews:"The book ? contains a very detailed and comprehensive description of MCMC methods useful for applied researchers. ? Undoubtedly the book is interesting ? . The reader will gain an extensive knowledge of the issues covered ? ." (Dimitris Karlis, Zentralblatt MATH, Vol. 1133 (11), 2008)"This new offering adds to our burgeoning Bayesian bookshelves a text directed at social scientists ? . To summarize, this a very useful text for a tightly bounded semester-long introduction to Bayesian statistics in the social sciences. The text is distinguished by its hands-on practical orientation which many readers will find very appealing. ? In addition, the book is handy for self-study ? ." (Jeff Gill, Journal of the American Statistical Association, Vol. 103 (483), September, 2008)?This book introduces readers to the world of Bayesian analysis and MCMC methods through brief discussions of theory, examples, and programming computations for pplications.