Research Methods in Applied Settings
An Integrated Approach to Design and Analysis, Third Edition
Routledge (Publisher)
3rd Edition
Published on 1. August 2016
Book
Paperback/Softback
576 pages
978-1-138-85301-0 (ISBN)
Description
Through its integrated approach to quantitative research methods, this text teaches readers how to plan, conduct, and write a research project and select and interpret data so they can become better consumers of research. This is not a statistics book-there are very few formulas. Rather, this book helps students master which statistic to use when and how to interpret the results. Organized around the steps one takes in conducting a research project, this book is ideal for applied programs and for those who want to analyze and evaluate research articles. Having taught in a variety of departments, the authors have a good grasp of the research problems faced by masters and doctoral students in diverse areas of the behavioral and social sciences.
Text adopters applaud the book's clarity. Students are often confused by other texts' use of inconsistent terminology. To avoid this confusion, the authors present a semantically consistent picture that emphasizes five research approaches-- randomized experimental, quasi-experimental, comparative, associational, and descriptive. The authors then show how these approaches lead to three kinds of research designs which, in turn, lead to three groups of statistics with the same names. This consistent framework increases comprehension and the ability to apply the material. Numerous applied problems, annotated examples, and diagrams and tables further promote comprehension. Although the book emphasizes quantitative research, the value of qualitative research is introduced. Each chapter also features boldfaced key terms, chapter introductions and summaries, interpretation questions, updated and additional examples, and boxes that highlight discussions of actual research projects from multiple disciplines.
This extensively revised edition features:
-A richer pedagogical plan including interpretation questions, 2-3 real-life examples per chapter, and boxes that highlight discussions of actual research projects from multiple disciplines.
-More coverage of research problems and reviewing the literature (Ch. 2).
-A new discussion on estimation for true score in classical test theory (ch 11) and how it is computed (ch 15).
-More of the basics on the traditional ways to think about measurement validity to clarify what is meant by evidence based response processes (ch 12).
-More information on conflict of interest and commitment, authorship, security of data, saving original files, and password protecting data files (ch 14).
-Expanded section on how conflict of interests can lead to bias in data coding and analysis along with suggestions for how to deal with potential bias (ch 14).
-New information on data transformations including how to use continuous data to create categorical data classifications such as high risk and low risk (ch. 15).
-Expanded section on different designs now includes a sample methods section and more information on multiple and logistic regression, mediation, and moderation analysis (ch. 22).
- A new table that highlights what to include in parts of an APA research paper (Ch 27).
-Updated list of suggested readings including contemporary articles and articles students can critique for class (Appendix A).
-A new appendix that includes 2-3 results write-up examples (Appendix G).
Text adopters applaud the book's clarity. Students are often confused by other texts' use of inconsistent terminology. To avoid this confusion, the authors present a semantically consistent picture that emphasizes five research approaches-- randomized experimental, quasi-experimental, comparative, associational, and descriptive. The authors then show how these approaches lead to three kinds of research designs which, in turn, lead to three groups of statistics with the same names. This consistent framework increases comprehension and the ability to apply the material. Numerous applied problems, annotated examples, and diagrams and tables further promote comprehension. Although the book emphasizes quantitative research, the value of qualitative research is introduced. Each chapter also features boldfaced key terms, chapter introductions and summaries, interpretation questions, updated and additional examples, and boxes that highlight discussions of actual research projects from multiple disciplines.
This extensively revised edition features:
-A richer pedagogical plan including interpretation questions, 2-3 real-life examples per chapter, and boxes that highlight discussions of actual research projects from multiple disciplines.
-More coverage of research problems and reviewing the literature (Ch. 2).
-A new discussion on estimation for true score in classical test theory (ch 11) and how it is computed (ch 15).
-More of the basics on the traditional ways to think about measurement validity to clarify what is meant by evidence based response processes (ch 12).
-More information on conflict of interest and commitment, authorship, security of data, saving original files, and password protecting data files (ch 14).
-Expanded section on how conflict of interests can lead to bias in data coding and analysis along with suggestions for how to deal with potential bias (ch 14).
-New information on data transformations including how to use continuous data to create categorical data classifications such as high risk and low risk (ch. 15).
-Expanded section on different designs now includes a sample methods section and more information on multiple and logistic regression, mediation, and moderation analysis (ch. 22).
- A new table that highlights what to include in parts of an APA research paper (Ch 27).
-Updated list of suggested readings including contemporary articles and articles students can critique for class (Appendix A).
-A new appendix that includes 2-3 results write-up examples (Appendix G).
More details
Edition
3rd edition
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
Professional and scholarly
Edition type
Revised edition
Illustrations
47 s/w Tabellen, 58 s/w Abbildungen
47 Tables, black and white; 58 Illustrations, black and white
Dimensions
Height: 254 mm
Width: 178 mm
ISBN-13
978-1-138-85301-0 (9781138853010)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Content
1. Definitions, Purposes, and Dimensions of Research 2. Planning a Quantitative Research Project Part 2: Quantitative Research Approaches, Questions, and Designs 3. Variables, Research Questions, and Hypotheses 4. Research Approaches 5. Randomized Experimental and Quasi-Experimental Designs 6. Single-Subject Designs 7. Non-experimental Approaches/Designs 8. Internal Validity Part 3: Sampling, Measurement and Data Collection 9. Sampling and Introduction to External Validity 10. Measurement and Descriptive Statistics 11. Measurement Reliability 12. Measurement Validity 13. Types of Data Collection Techniques 14. Ethical Issues in Conducting the Study 15. Practical Issues in Data Collection and Coding Part 4: Data Analysis and Interpretation 16. Making Inferences from Sample Data I: The Null Hypothesis Significance Testing Approach 17. Making Inferences From Sample Data II: The Evidence-Based Approach 18. General Design Classifications for Selection of Difference Statistical Methods 19. Selection of Appropriate Statistical Methods: Integration of Design and Analysis 20. Data Analysis and Interpretation - Basic Difference Questions 21. Analysis and Interpretation of Basic Associational Research Questions 22. Analysis and Interpretation of Complex Research Questions Part 5: Evaluating and Writing Research Reports 23. Evaluating Research Validity: Part I 24. Evaluating Research Validity: Part II 25. Evaluating Research for Evidence-Based Practice 26. Writing the Research Report