David Pevalin – författare

Where do I start? How do I know if I’m asking the right questions? How do I analyze the data once I have it? How do I report the results? When will I ever understand the process? If you are new to using the Stata software, and concerned about applying it to a project, help is at hand. David Pevalin and Karen Robson offer you a step by step introduction to the basics of the software, before gently helping you develop a more sophisticated understanding of Stata and its capabilities.

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:

Manipulating and organizing data Generating statistics Interpreting results Presenting outputs The Stata Survival Manual is a lifesaver for both students and professionals who are using the Stata software!

'This book is well referenced, excellently produced, and deserves wide consultation' - International Journal of Market Research

'Health researchers in the US and globally would do well to study this book and consider its implications for monitoring and analyzing socioeconomic inequalities in health within and across diverse countries' - Journal of Public Health Policy

As a result of a review conducted by the Economic and Social Research Council (ESRC) and the Office for National Statistics (ONS), both previous government social classifications, Social Class based on Occupation and Socio-economic Groups, were replaced in 2001 by a new classification, the National Statistics Socio-Economic Classification (NS-SEC). This book arises from original research, including primary data collection, undertaken by ESRC for ONS. There is a foreword from Gordon Marshall the Chief Executive of the ESRC.

This book introduces researchers to all aspects of the new classification. In particular, it:

- Fully describes the NS-SEC and elucidates its conceptual basis

- Guides readers in how the NS-SEC has been validated as a measure

- Evaluates how well NS-SEC works in describing and explaining the relationships between social class and key health and employment variables

- Demonstrates the applications of NS-SEC in research

The book will be required reading for all users of government social classifications. Its contents will also be of interest to sociologists concerned with the study of social inequality and courses in health inequality. Because of its inherent methodological interest the book will also be relevant to third year undergraduate and graduate courses that discuss how social scientists construct and validate basic measures.

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.