Jeffrey R. Wilson – författare

It is widely acknowledged that the hit franchise Game of Thrones is based on the Wars of the Roses, a bloody fifteenth-century civil war between feuding English families. In this book, Jeffrey R. Wilson shows how that connection was mediated by Shakespeare, and how a knowledge of the Shakespearean context enriches our understanding of the literary elements of Game of Thrones.

On the one hand, Shakespeare influenced Game of Thrones indirectly because his history plays significantly shaped the way the Wars of the Roses are now remembered, including the modern histories and historical fictions George R.R. Martin drew upon. On the other, Game of Thrones also responds to Shakespeare’s first tetralogy directly by adapting several of its literary strategies (such as shifting perspectives, mixed genres, and metatheater) and tropes (including the stigmatized protagonist and the prince who was promised). Presenting new interviews with the Game of Thrones cast, and comparing contextual circumstances of composition—such as collaborative authorship and political currents—this book also lodges a series of provocations about writing and acting for the stage in the Elizabethan age and for the screen in the twenty-first century.

An essential read for fans of the franchise, as well as students and academics looking at Shakespeare and Renaissance literature in the context of modern media.

It is widely acknowledged that the hit franchise Game of Thrones is based on the Wars of the Roses, a bloody fifteenth-century civil war between feuding English families. In this book, Jeffrey R. Wilson shows how that connection was mediated by Shakespeare, and how a knowledge of the Shakespearean context enriches our understanding of the literary elements of Game of Thrones.

On the one hand, Shakespeare influenced Game of Thrones indirectly because his history plays significantly shaped the way the Wars of the Roses are now remembered, including the modern histories and historical fictions George R.R. Martin drew upon. On the other, Game of Thrones also responds to Shakespeare’s first tetralogy directly by adapting several of its literary strategies (such as shifting perspectives, mixed genres, and metatheater) and tropes (including the stigmatized protagonist and the prince who was promised). Presenting new interviews with the Game of Thrones cast, and comparing contextual circumstances of composition—such as collaborative authorship and political currents—this book also lodges a series of provocations about writing and acting for the stage in the Elizabethan age and for the screen in the twenty-first century.

An essential read for fans of the franchise, as well as students and academics looking at Shakespeare and Renaissance literature in the context of modern media.

This monograph provides a concise point of research topics and reference for modeling correlated response data with time-dependent covariates, and longitudinal data for the analysis of population-averaged models, highlighting methods by a variety of pioneering scholars. While the models presented in the volume are applied to health and health-related data, they can be used to analyze any kind of data that contain covariates that change over time. The included data are analyzed with the use of both R and SAS, and the data and computing programs are provided to readers so that they can replicate and implement covered methods. It is an excellent resource for scholars of both computational and methodological statistics and biostatistics, particularly in the applied areas of health. ​

This book is an updated edition of Modeling Binary Correlated Responses Using SAS, SPSS and R, and now it includes the use of STATA. It uses these Statistical tools to analyze correlated binary data, accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages, as well as showcase both traditional and new methods for application to health-related research. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Short tutorials are in the appendix, for readers interested in learning more about the languages.

Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, SPSS and STATA, allows for easy implementation by readers. Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.

Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects.  Researchers and graduate students in Statistics, Epidemiology, and Public Health will find this book particularly useful.