Mixed methods design and two common implementations.

• A. It uses qualitative data only but collects larger samples.
• B. It combines qualitative and quantitative data collection/analysis; convergent parallel and sequential explanatory are common.
• C. It uses quantitative data only with experimental designs.
• D. It analyzes data using only one method at a time.

Answer: (B)

Mixed methods research combines qualitative and quantitative approaches to provide a fuller understanding by integrating data collection and analysis from both types. This way you can leverage the strengths of each method and offset their limitations. Two common ways this is implemented are convergent parallel and sequential explanatory designs.

In a convergent parallel design, qualitative and quantitative data are collected simultaneously, analyzed separately, and then merged during interpretation to see how the results align or complement each other. In a sequential explanatory design, you begin with quantitative data collection and analysis, then follow up with qualitative data to help explain or elaborate the quantitative findings, often revealing why certain results occurred or adding deeper insight.

The other options don’t fit the idea of mixing methods: one describes using only qualitative data (even with larger samples), another describes only quantitative data with experimental designs, and one suggests analyzing with only one method at a time. These lack the integrated use of both qualitative and quantitative data that characterizes mixed methods designs.