Mixed Methods Research Software to Bring Qualitative and Quantitative Data Together

Mixed methods research combines quantitative and qualitative data to provide more in-depth answers to complex questions. This method is commonly used in disciplines and industries that collect data in both numerical and non-numerical, unstructured forms such as health, behavioral, and social sciences.

Instead of pitting qualitative vs. quantitative methods against each other, mixed methods research combines quantitative data collection methods with qualitative data collection methods to provide context to numerical data, clarity to reoccurring themes and trends, and credibility to conclusions. The four main types of mixed methods research are convergent parallel, embedded design, explanatory sequential, and exploratory sequential.

A common example of designing and conducting mixed methods research can be found in data collection. Often researchers will collect data by asking a mix of open-ended questions (qualitative data) and close-ended or multiple-choice questions (quantitative data), and often include participant data such as demographics, job titles, and sample size. Frequently collected data types in mixed media are interviews, focus groups, surveys, and the numerical data that reflects the participants and their responses.

Combining qualitative and quantitative data can occur at various stages of the process, such as collecting, analyzing, tracking, and presenting and still be considered mixed methods research.

In these ways, the benefits of mixed methods research are limitless as it helps bring clarity and a thorough understanding of the research topic at hand.