【2014】Selecting the Right Analyses for Your Data: Quantitative, Qualitative, and Mixed Methods

Book 图书名称：Selecting the Right Analyses for Your Data: Quantitative, Qualitative, and Mixed Methods
Author 作者：W. Paul Vogt PhD, Elaine R. Vogt MA, Dianne C. Gardner PhD, Lynne M. Haeffele PhD
Publisher 出版社：The Guilford Press
Page 页数：500
Publishing Date 出版时间：July 2014
Language 语言：English
Size 大小：3 MB
Format 格式：pdf文字版
ISBN:1462515762, 9781462515769
Edition: 第1版搜索过论坛，没有该文档


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.

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.


== Table of contents ==
Preface
General Introduction
I. Coding Data—by Design
1. Coding Survey Data
2. Coding Interview Data
3. Coding Experimental Data
4. Coding Data from Naturalistic and Participant Observations
5. Coding Archival Data
II. Analysis and Interpretation of Quantitative Data
6. Describing, Exploring, and Visualizing Your Data
7. What Methods of Statistical Inference to Use When
8. What Associational Statistics to Use When
9. Advanced Associational Methods and Analyses
10. Model Building and Selection : Quantitative Data
III. Analysis and Interpretation of Qualitative and Combined/Mixed Data
11. Inductive Analyses of Qualitative Data: Ethnographic Approaches and Grounded Theory
12. Deductive Analyses of Qualitative Data: Comparative Case Studies and Qualitative Comparative Analysis
13. Coding and Analyzing Data from Combined and Mixed Designs
14. Conclusion


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