Bring Qualitative and Quantitative Data Together to Tell the Whole Story
Lumivero supports both qualitative and quantitative research with a variety of software. However, when you need to combine the two methods—mixed method research—Lumivero’s solutions complement each other to support both sides of the equation.
The result: It’s easy to generate automated insights that incorporate the data from both methods into a complete report that deals with the “why” and the “how much".
By using Lumivero solutions to conduct your mixed methods research, you get the benefit of compatible, user-friendly software with the ability to uncover insights and answers to your complex questions through powerful data analytics software.
Combining Numbers with Sentiments to Create Clear Insights
What Is Mixed Methods Research?
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.
Key Features of Mixed Methods Research
Key Features of Mixed Methods Research
Ability to ask open-ended, close-ended, and multiple-choice questions
Allows researchers to collect data from all types of sources including case studies, interviews, surveys, historical data, and more
Generate a more wholistic understanding of the research topic
Clearly communicate findings through charts, graphs, and quotes
Provide increased support to overall conclusion
The Complete Picture
Qualitative and quantitative research support and complement each other, as long as they integrate effectively. Let the numbers validate the sentiments and let the “why” explain the “what.” Lumivero solutions let you combine the two, so both perspectives are part of the insights being created.
Another mixed methods research example is if you conduct interviews and focus groups that utilize open-ended and multiple-choice questions, you can organize and identify themes in your qualitative data with NVivo and Citavi. Then, by pulling the numerical data on the themes, key words, and multiple-choice questions into XLSTAT, you can dig deeper into the data and create presentation-ready reports.
Insights Uncover Insights and Sentiment with Lumivero’s Qualitative Analysis Tools
By leveraging automation, qualitative researchers have more time to analyze their data. NVivo 14 saves researchers time looking for trends and identifying common categories to find the key themes in research. Qualitative researchers will have more time to analyze while their focus group research and in-depth interviews generate data for rigorous findings.
Analyze and Make Better Decisions with Lumivero’s Quantitative Analysis Tools
Once you analyze your qualitative data in NVivo 14, you may wish to query it against quantitative data from Lumivero's (or a third party's) quantitative analysis tool. NVivo 14 enables you to export such data to query it, run regressions, and generate codes and insights that leverage both types of data.
For example, you can directly import demographic or other classification sheets from Lumivero’s XLSTAT quantitative analysis software (or 3rd-party packages like SPSS) into NVivo, then run direct queries using the data as attributes.
While quantitative researchers prefer hard data to the kinds of open-ended responses that come from focus groups, surveys, and interviews, the qualitative data can provide context to numerical data. Lumivero supports mixed-method analysis by making qualitative data usable for quantitative analysis. For example, NVivo 14 uses algorithms to generate categories and codes which can be exported for use with Lumivero’s quantitative analysis solutions.
And it works both ways. For example, you can perform analysis in XLSTAT, then import your quantitative data into NVivo projects, leveraging that data as attributes for even more powerful qualitative insights.
By combining qualitative and quantitative data analysis, Lumivero lets you uncover the “how much” and also the “why.”
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.
