This timely and accomplished book offers readers a well informed, reliable guide to all aspects of qualitative secondary analysis.
· Defines secondary analysis
· Distinguishes between quantitative and qualitative secondary analysis
· Maps the main types of qualitative secondary analysis
· Covers the key ethical and legal issues
· Offers a practical guide to effective research
· Sets the agenda for future developments in the subject
Written by an experienced researcher and teacher with a background in sociology, the book is a comprehensive and invaluable introduction to this growing field of social research.
New to this Edition:
The latest advances in research methods are woven into the text from over 90 new research articles and books, covering topic like guidelines for writing research questions; distinguishing conceptual frameworks; techniques of video ethnography; abductive analysis; the value of systematic literature reviews and new human subjects rules; concerns about replicability and publication bias; and the rise of predatory journals. The rapidly increasing role of the Internet in both social relations and social research is reflected in new sections on systematic literature reviews, advances in online survey methods, geodata, digital ethnography, web experiments, online qualitative research, and new sources of big data. Current examples using research on pressing social issues such as inequality, healthcare, and police behavior offer students illustrate how social research contributes to understanding issues that are in the news and shaping their world.
This innovative book critically evaluates widely used sampling strategies, identifying key theoretical assumptions and considering how empirical and theoretical claims are made from these diverse methods.
Nick Emmel presents a groundbreaking reworking of sampling and choosing cases in qualitative research. Drawing on international case studies from across the social sciences he shows how ideas drive choices, how cases are used to work out the relation between ideas and evidence, and why it is not the size of a sample that matters, it is how cases are used to interpret and explain that counts.
Fresh, dynamic and timely, this book is essential reading for researchers and postgraduate students engaging with sampling and realism in qualitative research.
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.
Johnny Saldaña’s unique and invaluable manual demystifies the qualitative coding process with a comprehensive assessment of different coding types, examples and exercises. The ideal reference for students, teachers, and practitioners of qualitative inquiry, it is essential reading across the social sciences and neatly guides you through the multiple approaches available for coding qualitative data.
Its wide array of strategies, from the more straightforward to the more complex, is skillfully explained and carefully exemplified providing a complete toolkit of codes and skills that can be applied to any research project. For each code Saldaña provides information about the method's origin, gives a detailed description of the method, demonstrates its practical applications, and sets out a clearly illustrated example with analytic follow-up.
Now with a companion website, the book is supported by:
This international bestseller is an extremely usable, robust manual and is a must-have resource for qualitative researchers at all levels.
Click here for a listing of Johnny Saldaña's upcoming workshops.
Keeping the uniquely humorous and self-deprecating style that has made students across the world fall in love with Andy Field's books, Discovering Statistics Using R takes students on a journey of statistical discovery using R, a free, flexible and dynamically changing software tool for data analysis that is becoming increasingly popular across the social and behavioural sciences throughout the world.
The journey begins by explaining basic statistical and research concepts before a guided tour of the R software environment. Next you discover the importance of exploring and graphing data, before moving onto statistical tests that are the foundations of the rest of the book (for example correlation and regression). You will then stride confidently into intermediate level analyses such as ANOVA, before ending your journey with advanced techniques such as MANOVA and multilevel models. Although there is enough theory to help you gain the necessary conceptual understanding of what you're doing, the emphasis is on applying what you learn to playful and real-world examples that should make the experience more fun than you might expect.
Like its sister textbooks, Discovering Statistics Using R is written in an irreverent style and follows the same ground-breaking structure and pedagogical approach. The core material is augmented by a cast of characters to help the reader on their way, together with hundreds of examples, self-assessment tests to consolidate knowledge, and additional website material for those wanting to learn more.
Given this book's accessibility, fun spirit, and use of bizarre real-world research it should be essential for anyone wanting to learn about statistics using the freely-available R software.
The multimedia courseware provides tutorial work on sampling, basic statistics, and techniques for seeking information from databases and other sources. The statistics modules can be used as either part of a detective games or directly in teaching and learning. Brief video lessons in SPSS, using real datasets, are also a feature of the CD-ROM.
Why would you choose Introduction to Quantitative Research Methods
- It is theoretical, providing a concise overview of issues of quantitative research.
- It is practical, providing case studies that exemplify the different ways of research is conducted in the social sciences (ranging from psychology to sociology, politics and media).
- It is educational, providing practical vignettes, and chapter highlights for revision.
- It is integrative, producing a typology of different ways of conducting quantitative research methods.
- It is international, providing case studies from a range of countries.
- It is innovative, providing multimedia tutorials on generic research and statistical skills.
- It is clear, concise and accessible.
Doing Statistics With SPSSis derived from the authors' many years of experience teaching undergraduates data handling using SPSS. It assumes no prior understanding beyond that of basic mathematical operations and is therefore suitable for anyone undertaking an introductory statistics course as part of a science based undergraduate programme. The text will: enable the reader to make informed choices about what statistical tests to employ; what assumptions are made in using a particular test; demonstrate how to execute the analysis using SPSS; and guide the reader in his/her interpretation of its output. Each chapter ends with an exercise and provides detailed instructions on how to run the analysis using SPSS release 10. Learning is further guided by pointing the reader to particular aspects of the SPSS output and by having the reader engage with specified items of information from the SPSS results.
This text is more complete than the alternatives that usually fall into one of two camps. They either provide an explanation of the concepts but no instructions on how to execute the analysis with SPSS, or they are a manual which instructs the reader on how to drive the software but with minimal explanation of what it all means. This book offers the best elements of both in a style that is economical and accessible.
Doing Statistics with SPSS will be essential reading for undergraduates in psychology and health-related disciplines, and likely to be of invaluable use to many other students in the social sciences taking a course in statistics.
Beginning with a presentation of random variables and the expected value of a random variable, the book covers such topics as: the definition of reliability as a coefficient and possible uses of a coefficient; the notion of parallel tests so as to make possible the estimation of a reliability coefficient for a set of measurements; what to do when parallel tests are not available; what factors affect the reliability coefficient; and how to estimate the
This fully revised, expanded and updated Second Edition of the best-selling textbook by Jane Fielding and Nigel Gilbert provides a comprehensive yet accessible guide to quantitative data analysis. Designed to help take the fear out of the use of numbers in social research, this textbook introduces students to statistics as a powerful means of revealing patterns in human behaviour.
The textbook covers everything typically included in an introductory course on social statistics for students in the social sciences and the authors have taken the opportunity of this Second Edition to bring the data sources as current as possible. The book is full of up-to-date examples and useful and clear illustrations using the latest SPSS software.
While maintaining the student-friendly elements of the first, such as chapter summaries, exercises at the end of each chapter, and a glossary of key terms, new features to this edition include:
- Updated examples and references
SPSS coverage and screen-shots now incorporate the current version 14.0 and are used to demonstrate the latest social statistics datasets;
- Additions to content include a brand new section on developing a coding frame and an additional discussion of weighting counts as a means of analyzing published statistics;
- Enhanced design aids navigation which is further simplified by the addition of core objectives for each chapter and bullet-pointed chapter summaries;
- The updated Website at http:/www.soc.surrey.ac.uk/uss/index.html reflects changes made to the text and provides updated datasets;
A valuable and practical guide for students dealing with the large amounts of data that are typically collected in social surveys, the Second Edition of Understanding Social Statistics is an essential textbook for courses on statistics and quantitative research across the social sciences.
Addressing the perceived 'crisis of number' in a practical and fresh way the book sets out dynamic new approaches to teaching quantitative methods. It offers historical, comparative, analytical reflection and empirical evidence concerning the crisis in contemporary social sciences.
Experts from across the social sciences provide a wide range of authoritative insights as well as a number of useful illustrations of strategies and resources designed to help overcome this 'crisis of number'. Each chapter reflects the diversity of backgrounds and approaches within the social sciences making this an interdisciplinary, relevant addition to the subject.
The book also:
o focuses on innovations in how to teach quantitative research methods
o reports on the latest ESRC research projects on teaching quantitative methods
o locates itself within current debates about skills for employment.
Clear, engaging and original this book will be essential reading for those interested in learning and teaching quantitative methods.
Research Designsis a clear, compact introduction to the principles of experimental and non-experimental design especially written for social scientists and their students. Spector covers major designs including: single group designs; pre-test/post-test designs; factorial designs, hierarchical designs; multivariate designs; the Solomon four group design; panel designs; and designs with concomitant variables.
Snijders and Bosker's book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis.
This book provides step-by-step coverage of:
• multilevel theories
• ecological fallacies
• the hierarchical linear model
• testing and model specification
• study designs
• longitudinal data
• multivariate multilevel models
• discrete dependent variables
There are also new chapters on:
• missing data
• multilevel modeling and survey weights
• Bayesian and MCMC estimation and latent-class models.
This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix.
This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis.
Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen.
Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.
This book will prove to be equally useful for students conducting small research projects in the social sciences or related professional/applied areas, researchers planning systematic data collection for applied purposes and policy makers who want to understand and analyse the research with whose conclusions they are presented.
The new Sixth Edition of Making Sense of the Social World continues to be an unusually accessible and student-friendly introduction to the variety of social research methods, guiding undergraduate readers to understand research in their roles as consumers and novice producers of social science. Known for its concise, casual, and clear writing, its balanced treatment of quantitative and qualitative approaches, and its integrated approach to the fundamentals, the text has much to offer both novice researchers and more advanced students alike. The authors use a wide variety of examples from formal studies and everyday experiences to illustrate important principles and techniques.
New to this EditionFailure (and success) of pre-election polls in the 2016 Presidential election The use and abuse of data from social media such as Facebook and Twitter When does research on underprivileged populations become cultural appropriation? (based on the controversy over Alice Goffman’s ethnographic studies in Philadelphia) The debate over inclusion of U.S. citizenship questions on the 2020 Census The growth of new video techniques by researchers, and dramatically expanded use of web-based surveys (both by professionals and by students) Addition of material on methods widely used by student researchers, such as content analysis and “grounded theory” ethnography New vignettes on Research That Matters, Research in the News, and Careers and Research, to enhance the relevance of the book to undergraduates
This refreshing and accessible book provides students with a novel and useful resource for doing quantitative research. It offers students a guide on how to: interpret the complex reality of the social world; achieve effective measurement; understand the use of official statistics; use social surveys; understand probability and quantitative reasoning; interpret measurements; apply linear modelling; understand simulation and neural nets; and integrate quantitative and qualitative modelling in the research process.
Jargon-free and written with the needs of students in mind, the book will be required reading for students interested in using quantitative research methods.
This volume will enable researchers to execute Monte Carlo Simulation effectively and to interpret the estimated sampling distribution generated from its use.
The Second Edition is part of SAGE’s Quantitative Applications in the Social Sciences (QASS) series, which continues to serve countless students, instructors, and researchers in learning the most cutting-edge quantitative techniques.
The book is pedagogically well developed and contains many screen dumps and exercises, glossary terms and worked examples. Divided into two parts, Applied Statistics Using SPSS covers :
1. A self-study guide for learning how to use SPSS.
2. A reference guide for selecting the appropriate statistical technique and a stepwise do-it-yourself guide for analysing data and interpreting the results.
3. Readers of the book can download the SPSS data file that is used for most of the examples throughout the book here.
Geared explicitly for undergraduate needs, this is an easy to follow SPSS book that should provide a step-by-step guide to research design and data analysis using SPSS.
The SAGE Dictionary of Statisticsprovides students and researchers with an accessible and definitive resource to use when studying statistics in the social sciences, reading research reports and undertaking data analysis. Written by leading academics in the field of methodology and statistics, the Dictionary will be an essential study guide for the first-time researcher as well as a primary resource for more advanced study.
This is a practical and concise dictionary that serves the everyday uses of statistics across the whole range of social science disciplines. It offers basic and straightforward definitions of key concepts, followed by more detailed step-by-step explanations of situating specific methods and techniques. It also contains lists of related concepts to help the user to draw connections across various fields and increase their overall understand of a specific technique. A list of key readings helps to reinforce the aim of the Dictionary as an invaluable learning resource.
Designed specifically for students and those new to research, and written in a lively and engaging manner, this Dictionary is an essential reference work for students and researchers across the social sciences.
Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs.
The book also provides:Original case studies and data sets Practical guidance on how to run and test models in Stata Downloadable Stata programmes created to work alongside chapters A wide range of detailed applications using Stata Step-by-step notes on writing the relevant code.
This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.
Key features of the text:
Step-by-step instruction and screenshots
Designed to be hands-on with the user performing the analyses alongside on their computer as they read through each chapter
Call-out boxes provided, highlighting important information as appropriate
SPSS output explained, with written results provided using the popular, widely recognized APA format
End-of-chapter exercises included, allowing for additional practice
Features and updates to this edition include: material updated to IBM SPSS 24 (available Fall 2016), including screenshots and data sets/end-of-chapter exercises.
- Comprehensive guide informing how to use a range of advanced statistical methods such as MANOVA, path analysis and logistical regression;
- Inter-disciplinary: ideal for students studying upper level statistical methods in any subject across the social sciences;
- Practical guide: case studies, further reading, key terms explained in order to help the non-mathematically orientated student get ahead with their research.
Building on undergraduate statistical grounding, Understanding and Using Advanced Statistics provides the upper-level researcher with the knowledge of what advanced statistics do, how they should be used, and what their output means.