Mixed methodology : combining qualitative and quantitative approaches

書誌事項

Mixed methodology : combining qualitative and quantitative approaches

Abbas Tashakkori, Charles Teddlie

(Applied social research methods series, v. 46)

Sage Publications, c1998

  • : cloth
  • : pbk

この図書・雑誌をさがす
注記

Includes bibliographical references (p. 171-179) and index

内容説明・目次

内容説明

Looking for a practical guide to using mixed methodologies? Authors Abbas Tashakkori and Charles Teddlie explore the most resourceful way to combine qualitative and quantitative methodologies. Beginning with a discussion of the paradigm wars between positivism and constructivism, Mixed Methodology explains the differences between using mixed methods in only the research methodology portion of a study versus using mixed model studies across all phases of the research process, and then presents a typology of mixed methods and mixed model studies. The authors next examine sampling issues, reliability and validity questions, data collection procedures (including self-report techniques, questionnaires, observational methods, interaction analysis, and archival data/cultural artifacts), and data analysis techniques. Tashakkori and Teddlie conclude with detailed examples of current published and unpublished research that utilize mixed approaches. Researchers wanting to learn how to think about and utilize mixed methods in their studies will find this an indispensable guide for their work.

目次

PART ONE: PARADIGMS AND POLITICS OF RESEARCH Introduction to Mixed Methods and Mixed Model Studies in the Social and Behavioral Sciences Pragmatism and the Choice of Research Strategy Research Design Issues for Mixed Method and Mixed Model Studies PART TWO: METHODS AND STRATEGIES OF RESEARCH Sampling, Measurement, and Quality of Inferences Data Collection Strategies and Research Procedures Alternatives to Traditional Data Analytic Strategies PART THREE: APPLICATIONS, EXAMPLES AND FUTURE DIRECTION OF MIXED MODEL RESEARCH Examples of Mixed Model Designs Extended Examples of Mixed Model Designs Conclusions and Future Directions

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