Selecting the Right Analyses for Your Data
Selecting the Right Analyses for Your Data

Author: W. Paul Vogt

Publisher: Guilford Publications

Published: 2014-05-19

Total Pages: 521

ISBN-13: 1462515762

DOWNLOAD EBOOK

"What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. Useful features for teaching or self-study: *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. Subject Areas/Keywords: analyses, coding, combined methods, data analysis, data collection, dissertation, graphical, interpretation, mixed methods, qualitative, quantitative, research analysis, research designs, research methods, social sciences, thesis, visual Audience: Researchers, instructors, and graduate students in a range of disciplines, including psychology, education, social work, sociology, health, and management; administrators and managers who need to make data-driven decisions"--

Selecting the Right Analyses for Your Data
Selecting the Right Analyses for Your Data

Author: W. Paul Vogt

Publisher: Guilford Publications

Published: 2014-04-30

Total Pages: 522

ISBN-13: 1462516041

DOWNLOAD EBOOK

What are the most effective methods to code and analyze data for a particular study? This thoughtful and engaging book reviews the selection criteria for coding and analyzing any set of data--whether qualitative, quantitative, mixed, or visual. The authors systematically explain when to use verbal, numerical, graphic, or combined codes, and when to use qualitative, quantitative, graphic, or mixed-methods modes of analysis. Chapters on each topic are organized so that researchers can read them sequentially or can easily "flip and find" answers to specific questions. Nontechnical discussions of cutting-edge approaches--illustrated with real-world examples--emphasize how to choose (rather than how to implement) the various analyses. The book shows how using the right analysis methods leads to more justifiable conclusions and more persuasive presentations of research results. User-Friendly Features *Chapter-opening preview boxes that highlight useful topics addressed. *End-of-chapter summary tables recapping the 'dos and don'ts' and advantages and disadvantages of each analytic technique. *Annotated suggestions for further reading and technical resources on each topic. See also Vogt et al.'s When to Use What Research Design, which addresses the design and sampling decisions that occur prior to data collection.

When to Use What Research Design
When to Use What Research Design

Author: W. Paul Vogt

Publisher: Guilford Press

Published: 2012-04-04

Total Pages: 402

ISBN-13: 1462503624

DOWNLOAD EBOOK

Systematic, practical, and accessible, this is the first book to focus on finding the most defensible design for a particular research question. Thoughtful guidelines are provided for weighing the advantages and disadvantages of various methods, including qualitative, quantitative, and mixed methods designs. The book can be read sequentially or readers can dip into chapters on specific stages of research (basic design choices, selecting and sampling participants, addressing ethical issues) or data collection methods (surveys, interviews, experiments, observations, archival studies, and combined methods). Many chapter headings and subheadings are written as questions, helping readers quickly find the answers they need to make informed choices that will affect the later analysis and interpretation of their data. Useful features include: *Easy-to-navigate part and chapter structure. *Engaging research examples from a variety of fields. *End-of-chapter tables that summarize the main points covered. *Detailed suggestions for further reading at the end of each chapter. *Integration of data collection, sampling, and research ethics in one volume. *Comprehensive glossary. See also Vogt et al.'s Selecting the Right Analyses for Your Data, which addresses the next steps in coding, analyzing, and interpreting data.

Data Collection
Data Collection

Author: W Paul Vogt

Publisher: SAGE Publications Limited

Published: 2010-09-14

Total Pages: 0

ISBN-13: 9781847879301

DOWNLOAD EBOOK

Data collection is the foundation of high quality research, but it is often given less attention than later steps in a research project, such as coding and analyzing data. You first have to take care to gather appropriate types of and amount of data, because making adjustments later in the project can be prohibitive. This major work focuses on this neglected aspect of the research process. It is divided into five main sections that correspond to the broad types of research design and their associated sampling methods. The five categories of research design used to organize the selection are: 1. Surveys 2. Interviews 3. Experiments 4. Observations, including ethnographic 5. Archival and public sources of data

Data Analysis for Social Science
Data Analysis for Social Science

Author: Elena Llaudet

Publisher: Princeton University Press

Published: 2022-11-29

Total Pages: 256

ISBN-13: 0691199434

DOWNLOAD EBOOK

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--

Qualitative Data Analysis
Qualitative Data Analysis

Author: Ian Dey

Publisher: Routledge

Published: 2003-09-02

Total Pages: 309

ISBN-13: 1134931468

DOWNLOAD EBOOK

Qualitative Data Analysis shows that learning how to analyse qualitative data by computer can be fun. Written in a stimulating style, with examples drawn mainly from every day life and contemporary humour, it should appeal to a wide audience.

Handbook of Statistical Analysis and Data Mining Applications
Handbook of Statistical Analysis and Data Mining Applications

Author: Ken Yale

Publisher: Elsevier

Published: 2017-11-09

Total Pages: 824

ISBN-13: 0124166458

DOWNLOAD EBOOK

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

The Coding Manual for Qualitative Researchers
The Coding Manual for Qualitative Researchers

Author: Johnny Saldana

Publisher: SAGE

Published: 2009-02-19

Total Pages: 282

ISBN-13: 1446200124

DOWNLOAD EBOOK

The Coding Manual for Qualitative Researchers is unique in providing, in one volume, an in-depth guide to each of the multiple approaches available for coding qualitative data. In total, 29 different approaches to coding are covered, ranging in complexity from beginner to advanced level and covering the full range of types of qualitative data from interview transcripts to field notes. For each approach profiled, Johnny Saldaña discusses the method’s origins in the professional literature, a description of the method, recommendations for practical applications, and a clearly illustrated example.

The Routledge Reviewer’s Guide to Mixed Methods Analysis
The Routledge Reviewer’s Guide to Mixed Methods Analysis

Author: Anthony J. Onwuegbuzie

Publisher: Routledge

Published: 2021-07-12

Total Pages: 407

ISBN-13: 1351395521

DOWNLOAD EBOOK

The Routledge Reviewer’s Guide to Mixed Methods Analysis is a groundbreaking edited book – the first devoted solely to mixed methods research analyses, or mixed analyses. Each of the 30 seminal chapters, authored by internationally renowned scholars, provides a simple and practical introduction to a method of mixed analysis. Each chapter demonstrates "how to conduct the analysis" in easy-to-understand language. Many of the chapters present new topics that have never been written before, and all chapters offer cutting-edge approaches to analysis. The book contains the following four sections: Part I Quantitative Approaches to Qualitative Data (e.g., factor analysis of text, multidimensional scaling of qualitative data); Part II Qualitative Approaches to Quantitative Data (e.g., qualitizing data, mixed methodological discourse analysis); Part III "Inherently" Mixed Analysis Approaches (e.g., qualitative comparative analysis, mixed methods social network analysis, social media analytics as mixed analysis, GIS as mixed analysis); and Part IV Use of Software for Mixed Data Analysis (e.g., QDA Miner, WordStat, MAXQDA, NVivo, SPSS). The audience for this book includes (a) researchers, evaluators, and practitioners who conduct a variety of research projects and who are interested in using innovative analyses that will allow them to extract more from their data; (b) academics, including faculty who would use this book in their scholarship, as well as in their graduate-level courses, and graduate students who need access to a comprehensive set of mixed analysis tools for their dissertations/theses and other research assignments and projects; and (c) computer-assisted data analysis software developers who are seeking additional mixed analyses to include within their software programs. Chapter 24 of this book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.

Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide
Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide

Author: Agency for Health Care Research and Quality (U.S.)

Publisher: Government Printing Office

Published: 2013-02-21

Total Pages: 236

ISBN-13: 1587634236

DOWNLOAD EBOOK

This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)