Karen Robson – författare

The book will guide you through the research process offering further reading where more complex decisions need to be made and giving 'real world' examples from a wide range of disciplines and anecdotes that clarify issues for readers. The book will help with:

The book will guide you through the research process offering further reading where more complex decisions need to be made and giving ''real world'' examples from a wide range of disciplines and anecdotes that clarify issues for readers. The book will help with:

Have you been told you need to do multilevel modeling, but you can't get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense?

Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated.  This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.

Have you been told you need to do multilevel modeling, but you can't get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense?

Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated.  This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.

Pierre Bourdieu’s contributions to the theory and practice of social research are far reaching. Possibly the most prominent sociologist in recent times, his work has touched on a myriad of topics and has influenced scholars in multiple disciplines. Throughout Bourdieu’s work, emphasis is placed on the linkage between the practice of social research and its relationship to social theory. This book honours Bourdieu’s commitment to the inextricable relationship between social theory and research in social science. In this volume, authors from all over the world utilize key concepts coined by Bourdieu, specifically his concept of capitals, habitus, and the field, and attempt to test them using quantitative survey data.

The focus of this volume is how researchers can take key elements of Bourdieu’s work and apply them to the analysis of quantitative data on a variety of topics. Throughout the volume, issues of the possible interpretations of concepts and measurement validity are focused upon in a language that can be appreciated by new and experienced researchers alike. This volume is useful for courses where the linkage between theory and research is emphasized, at both the upper undergraduate and general postgraduate level. In addition to serving as a teaching tool, the articles within the volume will be invaluable to any scholar interested in working with Bourdieu’s concepts in quantitative research.

Have you been told you need to do multilevel modeling, but you can′t get past the forest of equations? Do you need the techniques explained with words and practical examples so they make sense?

Help is here! This book unpacks these statistical techniques in easy-to-understand language with fully annotated examples using the statistical software Stata. The techniques are explained without reliance on equations and algebra so that new users will understand when to use these approaches and how they are really just special applications of ordinary regression. Using real life data, the authors show you how to model random intercept models and random coefficient models for cross-sectional data in a way that makes sense and can be retained and repeated.  This book is the perfect answer for anyone who needs a clear, accessible introduction to multilevel modeling.