Mixed methods research #1 basic decisions and designs

Mixed methods research is built around one central requirement: qualitative and quantitative data must be combined to answer the same research question, with the two strands designed to complement each other rather than run in parallel. Instead of collecting interviews for one question and surveys for another, a mixed methods study deliberately brings both types of evidence into the same analytic and interpretive process—so findings from one strand can deepen, clarify, or explain patterns found in the other.

That core idea drives the major design decisions. One key choice is whether the study design is fixed or emergent. A fixed design commits from the outset to mixing qualitative and quantitative components. An emergent design starts with one approach—often qualitative data collection and analysis—and then adds a quantitative strand once new insights suggest it would strengthen the study.

Researchers also decide how much weight to give each strand. Options include qualitative priority, quantitative priority, or equal priority, which can shape whether the study is predominantly one approach with a supporting component, or whether both strands carry comparable influence.

Timing is another decisive factor. In a concurrent design, qualitative and quantitative data are collected and analyzed at the same time. In a sequential design, one strand comes first and the other follows—either qualitative first then quantitative, or the reverse. A multiphase design breaks the study into multiple stages, combining concurrent and sequential elements across phases.

Although there are many possible mixed methods designs—nearly 40—the discussion narrows to three widely used patterns. An explanatory design starts with quantitative data collection and analysis, then follows with qualitative data to probe surprising or interesting trends. After analyzing each strand separately, the study compares results and integrates them during interpretation.

An exploratory design flips that logic. It begins with qualitative data collection and analysis, then uses those insights to shape a subsequent quantitative instrument such as a questionnaire. Quantitative and qualitative results are analyzed separately, then merged during interpretation.

A convergent design collects qualitative and quantitative data simultaneously, merges the results, and compares findings directly—aiming to see how the two strands align or diverge.

Equally important is what mixed methods research is not. Simply using multiple data collection methods counts as mixed methods only if both qualitative and quantitative data are brought together to address the same research question. Likewise, having qualitative and quantitative data but reporting them separately—or using them to answer different questions—does not meet the mixed methods standard described here. The distinction is practical: mixed methods requires intentional integration, not just coexistence of two types of data.