Directives for Combining Qualitative and Quantitative Research Approaches
John W. Creswell and Vicki L. Plano Clark, renowned authors, published the seminal book "Designing and Conducting Mixed Methods Research" in 2007. This book offers valuable insights into this innovative research approach.
Mixed-methods research involves the collection of both qualitative and quantitative data, either simultaneously or in separate phases. This method offers a comprehensive view of a research topic, providing a richer understanding than either approach alone.
In the world of quantitative research, data is assigned values, checked for errors, recoded, and new variables created. Data is then prepared for analysis, and a codebook is created to document the variables and their values. Quantitative results are typically presented through statistical summaries, tables, and diagrams. Descriptive statistics offer an overview of trends, while inferential statistics help draw conclusions from the data.
On the other hand, qualitative data analysis involves manually coding data, assigning labels, combining similar codes, and identifying broader themes. Intercoder agreement is used to ensure the consistency of coding. Qualitative results are interpreted by summarizing key findings and explaining how they relate to the research questions.
Data analysis in a mixed-methods study involves establishing meaningful connections between quantitative and qualitative data to draw solid, insightful conclusions. Tables organize numerical results for easy comparison of variables, while diagrams and visuals, such as bar charts, scatter plots, or histograms, visually represent data distributions and relationships.
Creswell and Plano Clark (2016) emphasize the importance of focusing on the types of analyses (quantitative or qualitative) used to answer mixed-methods questions. In the exploratory phase, researchers examine general trends and preliminary data, read through all collected qualitative data, take notes, develop initial codes, and create a qualitative codebook. For quantitative data analysis, researchers choose appropriate inferential statistical tests based on the research questions, scale type, number of variables, and data distribution.
In the presenting data phase, researchers summarize and present results in the form of statements, tables, or visuals. Depending on the approach, they use diagrams, maps, or tables to represent results. Ensure consistency by following established style guidelines, such as APA formatting.
Validity takes precedence over reliability in qualitative research. Researchers assess whether the data is credible, transferable, dependable, and confirmable. In contrast, quantitative research relies on external standards to ensure validity and reliability, addressing construct validity, reliability, and external validity.
For those preparing qualitative data for analysis, transcribing recordings, checking for accuracy, formatting for analysis, categorizing the data, and formatting files for qualitative analysis software are essential steps. Similarly, to prepare quantitative data for analysis, researchers assign values to responses, check for data entry errors, recode items, calculate new variables, and create a codebook.
In a mixed-methods study, researchers can integrate their quantitative and qualitative insights and consider how they contribute to their research objectives. By understanding and applying these principles, researchers can conduct powerful, insightful mixed-methods studies that offer a comprehensive understanding of their research topics.
